>>Yeah, >>yeah. Hello, everyone. And welcome to the cultivating a data slowing culture. Jack, my name is Paula Johnson. I'm thought Spots head of community, and I am so excited to be your host heared at beyond. One of my favorite things about beyond is connecting with everyone and just feeling that buzz and energy from you all. So please don't be shy and engage in the chat. I'll be there shortly. We all know that when it comes to being fluent in a language, it's all about how do you take data in the sense and turn it into action? We've seen that in the hands of employees. Once they have access to this information, they are more engaged in their role. They're more productive, and most importantly, they're making better decisions. I think all of us want a little bit more of that, don't we? In today's track, you'll hear from expert partners and our customers and best practices that you could start applying to build that data. Fluent culture in your organization that we're seeing is powering the digital transformation across all industries will also discuss the role that the analysts of the future plays when it comes to this cultural shift and how important it is for diversity in data that helps us prevent bias at scale. To start us off our first session of the day is cultivating a data fluent culture, the essence and essentials. Our first speaker, CEO and founder of the Data Lodge, Valerie Logan. Valerie, Thank you for joining us today of passings over to you Now. >>Excellent. Thank you so much while it's so great to be here with the thought spot family. And there is nothing I would love to talk more about than data literacy and data fluency. And I >>just want to take a >>second and acknowledge I love how thought spot refers to this as data fluency and because I really see data literacy and fluency at, you know, either end of the same spectrum. And to mark that to commemorate that I have decorated the Scrabble board for today's occasion with fluency and literacy intersecting right at the center of the board. So with that, let's go ahead and get started and talking about how do you cultivate a data fluent culture? So in today's session, I am thrilled to be able to talk through Ah, few dynamics around what's >>going >>on in the market around this area. Who are the pioneers and what are they doing to drive data fluent culture? And what can you do about it? What are the best practices that you can apply to start this? This momentum and it's really a movement. So how do you want to play a part in this movement? So the market in the myths, um you know, it's 2020. We have had what I would call an unexpected awakening for the topic of data literacy and fluency. So let's just take a little trip down memory lane. So the last few years, data literacy and data fluency have been emerging as part of the chief data officer Agenda Analytics leaders have been looking at data culture, um, and the up skilling of the workforce as a key cornerstone to how do you create Ah, modern data and analytic strategy. But often this has been viewed as kind of just training or visualization or, um, a lot of focus on the upscaling side of data literacy. So there's >>been >>some great developments over the past few years with I was leading research at Gartner on this topic. There's other work around assessments and training Resource is. But if I'm if I'm really honest, they a lot of this has been somewhat viewed as academic and maybe a bit abstract. Enter the year 2020 where data literacy just got riel and it really can no longer be ignored. And the co vid pandemic has made this personal for all of us, not only in our work roles but in our personal lives, with our friends and families trying to make critical life decisions. So what I'd ask you to do is just to appreciate that this topic is no longer just a work thing. It is personal, and I think that's one of the ways you start to really crack. The culture code is how do you make this relevant to everyone in their personal lives? And unfortunately, cove it did that, and it has brought it to the forefront. But the challenge is how do you balance how do analytics leaders balance the need to up skill the workforce in the culture, with all of these competing needs around modernizing the platform and, um, driving trusted data and data governance? So that's what we'll be exploring is how to do this in parallel. So the very first thing that we need to do is start with the definition and I'd like to share with you how I framed data literacy for any industry across the globe. Which is first of all to appreciate that data literacy as a foundation capability has really been elevated now as >>an >>equivalent to people process and technology. And, you know, if you've been around a while, you know that classic trinity of people process and technology, It's the way that we have thought about how do you change an organization but with the digitization of our work, our lives, our society, you know anything from how do we consume information? How do we serve customers? Um, you know, we're walking sensors with our smartphones are worlds are digital now, and so data has been elevated as an equivalent Vector two people process and technology. And this is really why the role of the chief data officer in the analytics leader has been elevated to a C suite role. And it's also why data literacy and fluency is a workforce competency, not just for the specialist eso You know, I'm an old math major quant. So I've always kind of appreciated the role of data, but now it's prevalent to all right in work in life. So this >>is a >>mindset shift. And in addition to the mindset shift, let's look at what really makes up the elements of what does it mean to be data literate. So I like to call it the ability to read, write and communicate with data in context in both work in life and that it has two pieces. It has a vocabulary, so the vocabulary includes three basic sets of terms. So it includes data terms, obviously, so data sources, data attributes, data quality. There are analysis methods and concepts and terms. You know, it could be anything from, ah, bar Chart Thio, an advanced machine learning algorithm to the value drivers, right? The business acumen. What problems are resolving. So if you really break it down, it's those three sets of terms that make up the vocabulary. But it's not just the terms. It's also what we do with those terms and the skills and the skills. I like to refer to those as the acronym T T E a How do you think? How do you engage with others and how do you act or apply with data constructively? So hopefully that gives you a good basis for how we think about data literacy. And of course, the stronger you get in data literacy drives you towards higher degrees of data fluency. So I like to say we need to make this personal. And when we think about the different roles that we have in life and the different backgrounds that we bring, we think about the diversity and the inclusion of all people and all backgrounds. Diversity, to me is in addition to diversity of our gender identification, diversity of our racial backgrounds and histories. Diversity is also what is what is our work experience in our life experience. So one of the things I really like to do is to use this quote when talking about data literacy, which is we don't see things as they are. We see them as we are. So what we do is we create permission to say, you know what? It's okay that maybe you have some fear about this topic, or you may have some vulnerability around using, um you know, interactive dashboards. Um, you know, it's all about how we each come to this topic and how we support each other. So what I'd like to dio is just describe how we do that and the way that I like to teach that is this idea that we we foster data literacy by acknowledging that really, you learn this language, you learn this through embracing it, like learning a second language. So just take a second and think about you know what languages you speak right? And maybe maybe it's one. Maybe it's too often there's, you know, multiple. But you can embrace data literacy and fluency like it's a language, and somehow that creates permission for people to just say, you know, it's OK that I don't necessarily speak this language, but but I can try. So the way that we like to break this down and I call this SL information as a second language built off of the SL construct of English as a second language and it starts with that basic vocabulary, right? Every language has a vocabulary, and what I mentioned earlier in the definition is this idea that there are three basic sets of terms, value information and analysis. And everybody, when they're learning things like Stow have like a little pneumonic, right? So this is called the V A model, and you can take this and you can apply it to any use case. And you can welcome others into the conversation and say, You know, I really understand the V and the I, but I'm not a Kwan. I don't understand the A. So even just having this basic little triangle called the Via Model starts to create a frame for a shared conversation. But it's not just the vocabulary. It's also about the die elects. So if you are in a hospital, you talk about patient outcomes. If you are in insurance, you talk about underwriting and claims related outcomes. So the beauty of this language is there is a core construct for a vocabulary. But then it gets contextualized, and the beauty of that is, even if you're a classic business person that don't you don't think you're a data and analytics person. You bring something to the party. You bring something to this language, which is you understand the value drivers, so hopefully that's a good basis for you. But it's not just the language. It's also the constructs. How do you think? How do you interact and how do you add value? So here's a little double click of the T E. A acronym to show you it's Are you aware of context? So when you're watching the news, which could be interesting these days, are you actually stepping back and taking pause and saying E wonder what the source of that ISS? I wonder what the assumptions are or when you're in interacting with others. What is your degree of the ability? Thio? Tele Data story, Right? Do you have comfort and confidence interacting with others and then on the applying? This is at the end of the day, this is all about helping people make decisions. So when you're making a decision, are you being conscientious of the ethics right, the ethics or the potential bias in what you're looking at and what you're potentially doing? So I hope this provides you a nice frame. Just if you take nothing else away, take away the V A model as a way to think about a use case and application of data that there's different dialects. So when you're interacting with somebody, think of what dialect are they speaking? And then these three basic skill sets that were helping the workforce to up skill on. But the last thing is, um, you know, there's there's different levels of proficiency, and this is the point of literacy versus fluency. Depending on your role. Not everyone needs to speak data at the same level. So what we're trying to do is get everyone, at least to a shared level of conversational data, right? A basic level of foundation literacy. But based on your role, you will develop different degrees of fluency. The last point of treating this as a language is the idea that we don't just learn language through training. We learn language through interaction and experience. So I would encourage you. Just think about all what are all the different ways you can learn language and apply those to your relationship with data. Hopefully, that makes sense. Um, >>there's a >>few myths out there around this topic of data literacy, and I just want to do a little myth busting real quickly just so you can be on the lookout for these. So first of all data literacy is not about just about training. Training and assessments are certainly a cornerstone, however, when you think about developing a language, yeah, you can use a Rosetta Stone or one of those techniques, but that only gets you. So far. It's conversations you have. It's immersion. Eso keep in mind. It's not just about training. There are many ways to develop language. Secondly, data literacy is not just about internal structure, data and statistics. There are so many different types of data sets, audio, video, text, um, and so many different methods for synthesizing that content. So keep in mind, this isn't just about kind of classic data and methods. The third is visualization and storytelling are such a beautiful way to bring data literacy toe life. But it's not on Lee about visualization and storytelling, right? So there are different techniques. There are different methods on. We'll talk in a minute about health. Top Spot is embedding a lot of the data literacy capabilities into the environment. So it's not just about visualization and storytelling, and it's certainly not about making everybody a junior data scientist. The key is to identify, you know, if you are a call center representative. If you are a Knop orations manager, if you are the CEO, what is the appropriate profile of literacy and fluency for you? The last point and hopefully you get this by now is thistle is not just a work skill. And I think this is one of the best, um, services that we can provide to our employees is when you train an employee and help them up. Skill their data fluency. You're actually up Skilling, the household and their friends and their family because you're teaching them and then they can continue to teach. So at the >>end of >>the day, when we talk about what are the needs and drivers like, where's the return and what are the main objectives of, you know, having a C suite embrace state illiteracy as, ah program? There are primarily four key themes that come up that I hear all the time that I work with clients on Number one is This is how you help accelerate the shift to a data informed, insight driven culture. Or I actually like how thought spot refers to signals, right? So it's not even just insights. It's How do you distill all this noise right and and respond to the signals. But to do that collectively and culturally. Secondly, this is about unlocking what I call radical collaboration so well, while these terms often, sometimes they're viewed as, oh, we need to up skill the full population. This is as much about unlocking how data scientists, data engineers and business analysts collaborate. Right there is there is work to be done there, an opportunity there. The third is yes, we need to do this in the context of up Skilling for digital dexterity. So what I mean by that is data literacy and fluency is in the context of whole Siris of other up Skilling objectives. So becoming more agile understanding, process, automation, understanding, um, the broader ability, you know, ai and in Internet of things sensors, right? So this is part of a portfolio of up skilling. But at the end of the day, it comes down to comfort and confidence. If people are not comfortable with decision making in their role at their level in their those moments that matter, you won't get the kind of engagement. So this is also about fostering comfort and confidence. The last thing is, you know, you have so much data and analytics talent in your organization, and what we want to do is we want to maximize that talent. We really want to reduce dependency on reports and hey, can you can you put that together for me and really enable not just self service but democratizing that access and creating that freedom of access, but also freed up capacity. So if you're looking to build the case for a program, these air the primary four drivers that you can identify clear r A y and I call r o, I, I refer to are oh, I two ways return on investment and also risk of ignoring eso. You gotta be careful. You ignore these. They're going to come back to haunt you later. Eso Hopefully this helps you build the case. So let's take a look at what is a data literacy program. So it's one thing to say, Yeah, that sounds good, but how do you collectively and systemically start to enable this culture change? So, in pioneering data literacy programs, I like to call a data literacy program a commitment. Okay, this is an intentional commitment to up skill, the workforce in the culture, and there's really three pieces to that. The first is it has to be scoped to say we are about enabling the full potential of all associates. And sometimes some of my clients are extending that beyond the virtual walls of their organization to say S I'm working with a U. S. Federal agency. They're talking about data literacy for citizens, right, extending it outside the wall. So it's really about all your constituents on day and associates. Secondly, it is about fostering shared language and the modern data literacy abilities. The third is putting a real focus on what are the moments that matter. So with any kind of heavy change program, there's always a risk that it can. It can get very vague. So here's some examples of the moments that you're really trying to identify in the moments that matter. We do that through three things. I'll just paint those real quick. One is engagement. How do you engage with the leaders? How do you develop community and how do you drive communications? Secondly, we do that through development. We do that through language development, explicitly self paced learning and then of course, broader professional development and training. The third area enablement. This one is often overlooked in any kind of data literacy program. And this is where Thought spot is driving innovation left and right. This is about augmentation of the experience. So if we expect data literacy and data fluency to be developed Onley through training and not augmenting the experience in the environment, we will miss a huge opportunity. So thought spot one. The announcement yesterday with search assist. This is a beautiful example of how we are augmenting guided data literacy, right to support unending user in asking data rich questions and to not expect them to have to know all the forms and features is no different than how a GPS does not tell you. Latitude, longitude, a GPS tells you, Turn left, turn right. So the ability to augment that the way that thought spot does is so powerful. And one of my clients calls it data literacy by design. So how are we in designing that into the environment? And at the end of the day, the last and fourth lever of how you drive a program is you've gotta have someone orchestrating this change. So there is a is an art and a science to data literacy program development. So a couple of examples of pioneers So one pioneer nationwide building society, um, incredible work on how they are leveraging thought spot In particular, Thio have conversations with data. They are creating frictionless voyages with data, and they're using the spot I Q tool to recommend personalized insight. Right? This is an example of that enablement that I was just explaining. Second example, Red hat red hat. They like to describe this as going farther faster than with a small group of experts. They also refer to it as supporting data conversations again with that idea of language. So what's the difference between pioneers and procrastinators? Because what I'm seeing in the market right now is we've got these frontline pioneers who are driving these programs. But then there's kind of a d i Y do it yourself mentality going on. So I just wanted to share what I'm observing as this contrast. So procrastinators are kind of thinking I have no idea where they even start with us, whereas pioneers air saying, you know what, this is absolutely central. Let's figure it out procrastinators are saying. You know what? This probably isn't the right time for this program. Other things are more important and pioneers air like you know what? We don't have an option fast forward a year from now. Do we really think this is gonna organically change? This is pervasive to everything we dio procrastinators. They're saying I don't even know who to put in charge for this. And pioneers there saying this needs a lead. This needs someone focusing on it and a network of influencers. And then finally, procrastinators, They're generally going, you know, we're just gonna wing this and we'll just we'll stand up in academy. We'll put some courses together and pioneers air saying, You know what? We need to work smart. We need a launch, We need a leverage and we need to scale. So I hope that this has inspired you that, you know, there really are many ways to go forward, as FDR said, and only one way of standing still. So not taking an action is a choice. And there were, you know, it does have impact. So a couple of just quick things to wrap up one is how do you get started with the data literacy program, so I recommend seven steps. Who's your sponsor and who is the lead craft? Your case for change. Make it explicit. Developed that narrative craft a blueprint that's scalable but that has an initial plan where data literacy is part of not separate. Run some pilot workshops. These can be so fun and you can tackle the fear and vulnerability concern with really going after, Like how? How do we speak data across different diverse parts of the team. Thes are so fun. And what I find is when I teach people how to run a workshop like this, they absolutely want to repeat it and they get demand for more and more workshops launch pragmatically, right? We don't have any time or energy for big, expansive programs. Identify some quick winds, ignite the grassroots movement, low cost. There are many ways to do that. Engage the influencers right, ignite this bottom up movement and find ways to welcome all to the party. And then finally, you gotta think about scale right over time. This is a partnership with learning and development partnership with HR. This becomes the fabric of how do you onboard people. How do you sustain people? How do you develop? So the last thing I wanted to just caution you on is there's a few kind of big mistakes in this area. One is you have to be clear on what you're solving for, right? What does this really mean? What does it look like? What are the needs and drivers? Where is this being done? Well, today, to be very clear on what you're solving for secondly, language matters, right? If if that has not been clear, language is the common thread and it is the basis for literacy and fluency. Third, going it alone. If you try to tackle this and try to wing it. Google searching data literacy You will spend your time and energy, which is as precious of a currency as your money on efforts that, um, take more time. And there is a lot to be leveraged through through various partnerships and leverage of your vendor providers like thought spot. Last thing. A quick story. Um, over 100 years ago, Ford Motor Company think about think about who the worker population was in the plants. They were immigrants coming from all different countries having different native languages. What was happening in the environment in the plants is they were experiencing significant safety issues and efficiency issues. The root issue was lack of a shared language. I truly believe that we're at the same moment where we're lacking a shared language around data. So what Ford did was they created the Ford English school and they started to nurture that shared language. And I believe that that's exactly what we're doing now, right? So I couldn't I couldn't leave this picture, though, and not acknowledge. Not a lot of diversity in that room. So I know we would have more diversity now if we brought everyone together. But I just hope that this story resonates with you as the power of language as a foundation for growing literacy and fluency >>for joining us. We're actually gonna be jumping into the next section, so grab a quick water break, but don't wander too far. You definitely do not want to miss the second session of today. We're going to be exploring how to scale the impact and how to become a change agent in your organization and become that analysts of the future. So season

(soft music) >> Hello, everyone. Welcome to theCUBE's presentation of the AWS Startup Showcase. AI and Machine Learning: Top Startups Building Foundational Model Infrastructure. This is season 3, episode 1 of the ongoing series covering the exciting stuff from the AWS ecosystem, talking about machine learning and AI. I'm your host, John Furrier and today we are excited to be joined by Luis Ceze who's the CEO of OctoML and Anna Connolly, VP of customer success and experience OctoML. Great to have you on again, Luis. Anna, thanks for coming on. Appreciate it. >> Thank you, John. It's great to be here. >> Thanks for having us. >> I love the company. We had a CUBE conversation about this. You guys are really addressing how to run foundational models faster for less. And this is like the key theme. But before we get into it, this is a hot trend, but let's explain what you guys do. Can you set the narrative of what the company's about, why it was founded, what's your North Star and your mission? >> Yeah, so John, our mission is to make AI sustainable and accessible for everyone. And what we offer customers is, you know, a way of taking their models into production in the most efficient way possible by automating the process of getting a model and optimizing it for a variety of hardware and making cost-effective. So better, faster, cheaper model deployment. >> You know, the big trend here is AI. Everyone's seeing the ChatGPT, kind of the shot heard around the world. The BingAI and this fiasco and the ongoing experimentation. People are into it, and I think the business impact is clear. I haven't seen this in all of my career in the technology industry of this kind of inflection point. And every senior leader I talk to is rethinking about how to rebuild their business with AI because now the large language models have come in, these foundational models are here, they can see value in their data. This is a 10 year journey in the big data world. Now it's impacting that, and everyone's rebuilding their company around this idea of being AI first 'cause they see ways to eliminate things and make things more efficient. And so now they telling 'em to go do it. And they're like, what do we do? So what do you guys think? Can you explain what is this wave of AI and why is it happening, why now, and what should people pay attention to? What does it mean to them? >> Yeah, I mean, it's pretty clear by now that AI can do amazing things that captures people's imaginations. And also now can show things that are really impactful in businesses, right? So what people have the opportunity to do today is to either train their own model that adds value to their business or find open models out there that can do very valuable things to them. So the next step really is how do you take that model and put it into production in a cost-effective way so that the business can actually get value out of it, right? >> Anna, what's your take? Because customers are there, you're there to make 'em successful, you got the new secret weapon for their business. >> Yeah, I think we just see a lot of companies struggle to get from a trained model into a model that is deployed in a cost-effective way that actually makes sense for the application they're building. I think that's a huge challenge we see today, kind of across the board across all of our customers. >> Well, I see this, everyone asking the same question. I have data, I want to get value out of it. I got to get these big models, I got to train it. What's it going to cost? So I think there's a reality of, okay, I got to do it. Then no one has any visibility on what it costs. When they get into it, this is going to break the bank. So I have to ask you guys, the cost of training these models is on everyone's mind. OctoML, your company's focus on the cost side of it as well as the efficiency side of running these models in production. Why are the production costs such a concern and where specifically are people looking at it and why did it get here? >> Yeah, so training costs get a lot of attention because normally a large number, but we shouldn't forget that it's a large, typically one time upfront cost that customers pay. But, you know, when the model is put into production, the cost grows directly with model usage and you actually want your model to be used because it's adding value, right? So, you know, the question that a customer faces is, you know, they have a model, they have a trained model and now what? So how much would it cost to run in production, right? And now without the big wave in generative AI, which rightfully is getting a lot of attention because of the amazing things that it can do. It's important for us to keep in mind that generative AI models like ChatGPT are huge, expensive energy hogs. They cost a lot to run, right? And given that model usage growth directly, model cost grows directly with usage, what you want to do is make sure that once you put a model into production, you have the best cost structure possible so that you're not surprised when it's gets popular, right? So let me give you an example. So if you have a model that costs, say 1 to $2 million to train, but then it costs about one to two cents per session to use it, right? So if you have a million active users, even if they use just once a day, it's 10 to $20,000 a day to operate that model in production. And that very, very quickly, you know, get beyond what you paid to train it. >> Anna, these aren't small numbers, and it's cost to train and cost to operate, it kind of reminds me of when the cloud came around and the data center versus cloud options. Like, wait a minute, one, it costs a ton of cash to deploy, and then running it. This is kind of a similar dynamic. What are you seeing? >> Yeah, absolutely. I think we are going to see increasingly the cost and production outpacing the costs and training by a lot. I mean, people talk about training costs now because that's what they're confronting now because people are so focused on getting models performant enough to even use in an application. And now that we have them and they're that capable, we're really going to start to see production costs go up a lot. >> Yeah, Luis, if you don't mind, I know this might be a little bit of a tangent, but, you know, training's super important. I get that. That's what people are doing now, but then there's the deployment side of production. Where do people get caught up and miss the boat or misconfigure? What's the gotcha? Where's the trip wire or so to speak? Where do people mess up on the cost side? What do they do? Is it they don't think about it, they tie it to proprietary hardware? What's the issue? >> Yeah, several things, right? So without getting really technical, which, you know, I might get into, you know, you have to understand relationship between performance, you know, both in terms of latency and throughput and cost, right? So reducing latency is important because you improve responsiveness of the model. But it's really important to keep in mind that it often leads diminishing returns. Below a certain latency, making it faster won't make a measurable difference in experience, but it's going to cost a lot more. So understanding that is important. Now, if you care more about throughputs, which is the time it takes for you to, you know, units per period of time, you care about time to solution, we should think about this throughput per dollar. And understand what you want is the highest throughput per dollar, which may come at the cost of higher latency, which you're not going to care about, right? So, and the reality here, John, is that, you know, humans and especially folks in this space want to have the latest and greatest hardware. And often they commit a lot of money to get access to them and have to commit upfront before they understand the needs that their models have, right? So common mistake here, one is not spending time to understand what you really need, and then two, over-committing and using more hardware than you actually need. And not giving yourself enough freedom to get your workload to move around to the more cost-effective choice, right? So this is just a metaphoric choice. And then another thing that's important here too is making a model run faster on the hardware directly translates to lower cost, right? So, but it takes a lot of engineers, you need to think of ways of producing very efficient versions of your model for the target hardware that you're going to use. >> Anna, what's the customer angle here? Because price performance has been around for a long time, people get that, but now latency and throughput, that's key because we're starting to see this in apps. I mean, there's an end user piece. I even seeing it on the infrastructure side where they're taking a heavy lifting away from operational costs. So you got, you know, application specific to the user and/or top of the stack, and then you got actually being used in operations where they want both. >> Yeah, absolutely. Maybe I can illustrate this with a quick story with the customer that we had recently been working with. So this customer is planning to run kind of a transformer based model for tech generation at super high scale on Nvidia T4 GPU, so kind of a commodity GPU. And the scale was so high that they would've been paying hundreds of thousands of dollars in cloud costs per year just to serve this model alone. You know, one of many models in their application stack. So we worked with this team to optimize our model and then benchmark across several possible targets. So that matching the hardware that Luis was just talking about, including the newer kind of Nvidia A10 GPUs. And what they found during this process was pretty interesting. First, the team was able to shave a quarter of their spend just by using better optimization techniques on the T4, the older hardware. But actually moving to a newer GPU would allow them to serve this model in a sub two milliseconds latency, so super fast, which was able to unlock an entirely new kind of user experience. So they were able to kind of change the value they're delivering in their application just because they were able to move to this new hardware easily. So they ultimately decided to plan their deployment on the more expensive A10 because of this, but because of the hardware specific optimizations that we helped them with, they managed to even, you know, bring costs down from what they had originally planned. And so if you extend this kind of example to everything that's happening with generative AI, I think the story we just talked about was super relevant, but the scale can be even higher, you know, it can be tenfold that. We were recently conducting kind of this internal study using GPT-J as a proxy to illustrate the experience of just a company trying to use one of these large language models with an example scenario of creating a chatbot to help job seekers prepare for interviews. So if you imagine kind of a conservative usage scenario where the model generates just 3000 words per user per day, which is, you know, pretty conservative for how people are interacting with these models. It costs 5 cents a session and if you're a company and your app goes viral, so from, you know, beginning of the year there's nobody, at the end of the year there's a million daily active active users in that year alone, going from zero to a million. You'll be spending about $6 million a year, which is pretty unmanageable. That's crazy, right? >> Yeah. >> For a company or a product that's just launching. So I think, you know, for us we see the real way to make these kind of advancements accessible and sustainable, as we said is to bring down cost to serve using these techniques. >> That's a great story and I think that illustrates this idea that deployment cost can vary from situation to situation, from model to model and that the efficiency is so strong with this new wave, it eliminates heavy lifting, creates more efficiency, automates intellect. I mean, this is the trend, this is radical, this is going to increase. So the cost could go from nominal to millions, literally, potentially. So, this is what customers are doing. Yeah, that's a great story. What makes sense on a financial, is there a cost of ownership? Is there a pattern for best practice for training? What do you guys advise cuz this is a lot of time and money involved in all potential, you know, good scenarios of upside. But you can get over your skis as they say, and be successful and be out of business if you don't manage it. I mean, that's what people are talking about, right? >> Yeah, absolutely. I think, you know, we see kind of three main vectors to reduce cost. I think one is make your deployment process easier overall, so that your engineering effort to even get your app running goes down. Two, would be get more from the compute you're already paying for, you're already paying, you know, for your instances in the cloud, but can you do more with that? And then three would be shop around for lower cost hardware to match your use case. So on the first one, I think making the deployment easier overall, there's a lot of manual work that goes into benchmarking, optimizing and packaging models for deployment. And because the performance of machine learning models can be really hardware dependent, you have to go through this process for each target you want to consider running your model on. And this is hard, you know, we see that every day. But for teams who want to incorporate some of these large language models into their applications, it might be desirable because licensing a model from a large vendor like OpenAI can leave you, you know, over provision, kind of paying for capabilities you don't need in your application or can lock you into them and you lose flexibility. So we have a customer whose team actually prepares models for deployment in a SaaS application that many of us use every day. And they told us recently that without kind of an automated benchmarking and experimentation platform, they were spending several days each to benchmark a single model on a single hardware type. So this is really, you know, manually intensive and then getting more from the compute you're already paying for. We do see customers who leave money on the table by running models that haven't been optimized specifically for the hardware target they're using, like Luis was mentioning. And for some teams they just don't have the time to go through an optimization process and for others they might lack kind of specialized expertise and this is something we can bring. And then on shopping around for different hardware types, we really see a huge variation in model performance across hardware, not just CPU vs. GPU, which is, you know, what people normally think of. But across CPU vendors themselves, high memory instances and across cloud providers even. So the best strategy here is for teams to really be able to, we say, look before you leap by running real world benchmarking and not just simulations or predictions to find the best software, hardware combination for their workload. >> Yeah. You guys sound like you have a very impressive customer base deploying large language models. Where would you categorize your current customer base? And as you look out, as you guys are growing, you have new customers coming in, take me through the progression. Take me through the profile of some of your customers you have now, size, are they hyperscalers, are they big app folks, are they kicking the tires? And then as people are out there scratching heads, I got to get in this game, what's their psychology like? Are they coming in with specific problems or do they have specific orientation point of view about what they want to do? Can you share some data around what you're seeing? >> Yeah, I think, you know, we have customers that kind of range across the spectrum of sophistication from teams that basically don't have MLOps expertise in their company at all. And so they're really looking for us to kind of give a full service, how should I do everything from, you know, optimization, find the hardware, prepare for deployment. And then we have teams that, you know, maybe already have their serving and hosting infrastructure up and ready and they already have models in production and they're really just looking to, you know, take the extra juice out of the hardware and just do really specific on that optimization piece. I think one place where we're doing a lot more work now is kind of in the developer tooling, you know, model selection space. And that's kind of an area that we're creating more tools for, particularly within the PyTorch ecosystem to bring kind of this power earlier in the development cycle so that as people are grabbing a model off the shelf, they can, you know, see how it might perform and use that to inform their development process. >> Luis, what's the big, I like this idea of picking the models because isn't that like going to the market and picking the best model for your data? It's like, you know, it's like, isn't there a certain approaches? What's your view on this? 'Cause this is where everyone, I think it's going to be a land rush for this and I want to get your thoughts. >> For sure, yeah. So, you know, I guess I'll start with saying the one main takeaway that we got from the GPT-J study is that, you know, having a different understanding of what your model's compute and memory requirements are, very quickly, early on helps with the much smarter AI model deployments, right? So, and in fact, you know, Anna just touched on this, but I want to, you know, make sure that it's clear that OctoML is putting that power into user's hands right now. So in partnership with AWS, we are launching this new PyTorch native profiler that allows you with a single, you know, one line, you know, code decorator allows you to see how your code runs on a variety of different hardware after accelerations. So it gives you very clear, you know, data on how you should think about your model deployments. And this ties back to choices of models. So like, if you have a set of choices that are equally good of models in terms of functionality and you want to understand after acceleration how are you going to deploy, how much they're going to cost or what are the options using a automated process of making a decision is really, really useful. And in fact, so I think these events can get early access to this by signing up for the Octopods, you know, this is exclusive group for insiders here, so you can go to OctoML.ai/pods to sign up. >> So that Octopod, is that a program? What is that, is that access to code? Is that a beta, what is that? Explain, take a minute and explain Octopod. >> I think the Octopod would be a group of people who is interested in experiencing this functionality. So it is the friends and users of OctoML that would be the Octopod. And then yes, after you sign up, we would provide you essentially the tool in code form for you to try out in your own. I mean, part of the benefit of this is that it happens in your own local environment and you're in control of everything kind of within the workflow that developers are already using to create and begin putting these models into their applications. So it would all be within your control. >> Got it. I think the big question I have for you is when do you, when does that one of your customers know they need to call you? What's their environment look like? What are they struggling with? What are the conversations they might be having on their side of the fence? If anyone's watching this, they're like, "Hey, you know what, I've got my team, we have a lot of data. Do we have our own language model or do I use someone else's?" There's a lot of this, I will say discovery going on around what to do, what path to take, what does that customer look like, if someone's listening, when do they know to call you guys, OctoML? >> Well, I mean the most obvious one is that you have a significant spend on AI/ML, come and talk to us, you know, putting AIML into production. So that's the clear one. In fact, just this morning I was talking to someone who is in life sciences space and is having, you know, 15 to $20 million a year cloud related to AI/ML deployment is a clear, it's a pretty clear match right there, right? So that's on the cost side. But I also want to emphasize something that Anna said earlier that, you know, the hardware and software complexity involved in putting model into production is really high. So we've been able to abstract that away, offering a clean automation flow enables one, to experiment early on, you know, how models would run and get them to production. And then two, once they are into production, gives you an automated flow to continuously updating your model and taking advantage of all this acceleration and ability to run the model on the right hardware. So anyways, let's say one then is cost, you know, you have significant cost and then two, you have an automation needs. And Anna please compliment that. >> Yeah, Anna you can please- >> Yeah, I think that's exactly right. Maybe the other time is when you are expecting a big scale up in serving your application, right? You're launching a new feature, you expect to get a lot of usage or, and you want to kind of anticipate maybe your CTO, your CIO, whoever pays your cloud bills is going to come after you, right? And so they want to know, you know, what's the return on putting this model essentially into my application stack? Am I going to, is the usage going to match what I'm paying for it? And then you can understand that. >> So you guys have a lot of the early adopters, they got big data teams, they're pushed in the production, they want to get a little QA, test the waters, understand, use your technology to figure it out. Is there any cases where people have gone into production, they have to pull it out? It's like the old lemon laws with your car, you buy a car and oh my god, it's not the way I wanted it. I mean, I can imagine the early people through the wall, so to speak, in the wave here are going to be bloody in the sense that they've gone in and tried stuff and get stuck with huge bills. Are you seeing that? Are people pulling stuff out of production and redeploying? Or I can imagine that if I had a bad deployment, I'd want to refactor that or actually replatform that. Do you see that too? >> Definitely after a sticker shock, yes, your customers will come and make sure that, you know, the sticker shock won't happen again. >> Yeah. >> But then there's another more thorough aspect here that I think we likely touched on, be worth elaborating a bit more is just how are you going to scale in a way that's feasible depending on the allocation that you get, right? So as we mentioned several times here, you know, model deployment is so hardware dependent and so complex that you tend to get a model for a hardware choice and then you want to scale that specific type of instance. But what if, when you want to scale because suddenly luckily got popular and, you know, you want to scale it up and then you don't have that instance anymore. So how do you live with whatever you have at that moment is something that we see customers needing as well. You know, so in fact, ideally what we want is customers to not think about what kind of specific instances they want. What they want is to know what their models need. Say, they know the SLA and then find a set of hybrid targets and instances that hit the SLA whenever they're also scaling, they're going to scale with more freedom, right? Instead of having to wait for AWS to give them more specific allocation for a specific instance. What if you could live with other types of hardware and scale up in a more free way, right? So that's another thing that we see customers, you know, like they need more freedom to be able to scale with whatever is available. >> Anna, you touched on this with the business model impact to that 6 million cost, if that goes out of control, there's a business model aspect and there's a technical operation aspect to the cost side too. You want to be mindful of riding the wave in a good way, but not getting over your skis. So that brings up the point around, you know, confidence, right? And teamwork. Because if you're in production, there's probably a team behind it. Talk about the team aspect of your customers. I mean, they're dedicated, they go put stuff into production, they're developers, there're data. What's in it for them? Are they getting better, are they in the beach, you know, reading the book. Are they, you know, are there easy street for them? What's the customer benefit to the teams? >> Yeah, absolutely. With just a few clicks of a button, you're in production, right? That's the dream. So yeah, I mean I think that, you know, we illustrated it before a little bit. I think the automated kind of benchmarking and optimization process, like when you think about the effort it takes to get that data by hand, which is what people are doing today, they just don't do it. So they're making decisions without the best information because it's, you know, there just isn't the bandwidth to get the information that they need to make the best decision and then know exactly how to deploy it. So I think it's actually bringing kind of a new insight and capability to these teams that they didn't have before. And then maybe another aspect on the team side is that it's making the hand-off of the models from the data science teams to the model deployment teams more seamless. So we have, you know, we have seen in the past that this kind of transition point is the place where there are a lot of hiccups, right? The data science team will give a model to the production team and it'll be too slow for the application or it'll be too expensive to run and it has to go back and be changed and kind of this loop. And so, you know, with the PyTorch profiler that Luis was talking about, and then also, you know, the other ways we do optimization that kind of prevents that hand-off problem from happening. >> Luis and Anna, you guys have a great company. Final couple minutes left. Talk about the company, the people there, what's the culture like, you know, if Intel has Moore's law, which is, you know, doubling the performance in few years, what's the culture like there? Is it, you know, more throughput, better pricing? Explain what's going on with the company and put a plug in. Luis, we'll start with you. >> Yeah, absolutely. I'm extremely proud of the team that we built here. You know, we have a people first culture, you know, very, very collaborative and folks, we all have a shared mission here of making AI more accessible and sustainable. We have a very diverse team in terms of backgrounds and life stories, you know, to do what we do here, we need a team that has expertise in software engineering, in machine learning, in computer architecture. Even though we don't build chips, we need to understand how they work, right? So, and then, you know, the fact that we have this, this very really, really varied set of backgrounds makes the environment, you know, it's say very exciting to learn more about, you know, assistance end-to-end. But also makes it for a very interesting, you know, work environment, right? So people have different backgrounds, different stories. Some of them went to grad school, others, you know, were in intelligence agencies and now are working here, you know. So we have a really interesting set of people and, you know, life is too short not to work with interesting humans. You know, that's something that I like to think about, you know. >> I'm sure your off-site meetings are a lot of fun, people talking about computer architectures, silicon advances, the next GPU, the big data models coming in. Anna, what's your take? What's the culture like? What's the company vibe and what are you guys looking to do? What's the customer success pattern? What's up? >> Yeah, absolutely. I mean, I, you know, second all of the great things that Luis just said about the team. I think one that I, an additional one that I'd really like to underscore is kind of this customer obsession, to use a term you all know well. And focus on the end users and really making the experiences that we're bringing to our user who are developers really, you know, useful and valuable for them. And so I think, you know, all of these tools that we're trying to put in the hands of users, the industry and the market is changing so rapidly that our products across the board, you know, all of the companies that, you know, are part of the showcase today, we're all evolving them so quickly and we can only do that kind of really hand in glove with our users. So that would be another thing I'd emphasize. >> I think the change dynamic, the power dynamics of this industry is just the beginning. I'm very bullish that this is going to be probably one of the biggest inflection points in history of the computer industry because of all the dynamics of the confluence of all the forces, which you mentioned some of them, I mean PC, you know, interoperability within internetworking and you got, you know, the web and then mobile. Now we have this, I mean, I wouldn't even put social media even in the close to this. Like, this is like, changes user experience, changes infrastructure. There's going to be massive accelerations in performance on the hardware side from AWS's of the world and cloud and you got the edge and more data. This is really what big data was going to look like. This is the beginning. Final question, what do you guys see going forward in the future? >> Well, it's undeniable that machine learning and AI models are becoming an integral part of an interesting application today, right? So, and the clear trends here are, you know, more and more competitional needs for these models because they're only getting more and more powerful. And then two, you know, seeing the complexity of the infrastructure where they run, you know, just considering the cloud, there's like a wide variety of choices there, right? So being able to live with that and making the most out of it in a way that does not require, you know, an impossible to find team is something that's pretty clear. So the need for automation, abstracting with the complexity is definitely here. And we are seeing this, you know, trends are that you also see models starting to move to the edge as well. So it's clear that we're seeing, we are going to live in a world where there's no large models living in the cloud. And then, you know, edge models that talk to these models in the cloud to form, you know, an end-to-end truly intelligent application. >> Anna? >> Yeah, I think, you know, our, Luis said it at the beginning. Our vision is to make AI sustainable and accessible. And I think as this technology just expands in every company and every team, that's going to happen kind of on its own. And we're here to help support that. And I think you can't do that without tools like those like OctoML. >> I think it's going to be an error of massive invention, creativity, a lot of the format heavy lifting is going to allow the talented people to automate their intellect. I mean, this is really kind of what we see going on. And Luis, thank you so much. Anna, thanks for coming on this segment. Thanks for coming on theCUBE and being part of the AWS Startup Showcase. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>Good Morning Cloud community and welcome back to Fabulous Las Vegas, Nevada, where we are at AWS Reinvent. It is day four here on the Cube. I'm Savannah Peterson with Lisa Martin. You are looking fantastic. Day four, we've done 45 interviews. How are you feeling? Oh, >>Great. I can't believe it's day four. The cube will be producing over 100 interviews. >>Impressive. Right >>On this stage where there are two sets, and of course we have the set upstairs as well. It's amazing how much content we've created, how many great conversations we've had, right? And the excitement around AWS and the, and the community. >>Yeah. I feel like we've learned so much together. Love co-hosting with you, and so excited for our first conversation this morning with Wira. Welcome, Tim and Kashmira, welcome to the show. How you doing? You both look great for day four. Thank >>You. Yeah, we're doing good. Great. We're doing good. Ready to go. Day four, let's go. >>That's the spirit. That's exactly the energy we need here on the cube. So just in case someone in the audience is not familiar, tell us about Wipro. >>So Wipro is a global consulting company and we help transform our customers and their businesses. >>Transformation's been a super hot topic here at the show, quite frankly a big priority, especially with cost cutting and everything else that's going on. How, how do you do that? How do you help customers do that? Has >>Me run? So we, we, so we have our A strategy, which we call our full stride cloud strategy. So particularly from a cloud perspective here, obviously with aws, we have end to end client services. So from high end strategic consulting through customer journeys, technology implementation, all the way through to our managed services. So we help customers with the end to end journey, particularly as here we're talking about cloud, but also business transformation as well. And we have, you know, a whole host of technologies. So about a few years ago we made an announcement around a billion investment in cloud casual and that Yeah, absolutely. A cool billion and just a cool billion. Yeah. And that pocket >>Change. Exactly. >>Right. And that investment. Over the last few years, we've acquired a number of really exciting companies like Capco, which is a consulting company in the financial services space. We've acquired design companies, a company called Design it, looking at customer journeys and user experience, and then also technology companies called Rising, which looks after the whole SAP space. So we've kind of got the end to end solutions and technologies. And then we also invest in what we call Wipro Ventures. These are really innovative, exciting startups. We invest in those companies to really drive transformation. And the final thing that really brings the whole thing together is that we have decades of experience in engineering. That's kind of the heart of where we come from. So that experience all of that together really helps our clients to transform their business. And particularly as we're talking about cloud helps us to transform the cloud. Now what we are really hoping is that we can help our clients become what we call intelligent enterprises, and we are focusing more and more on customer outcomes and really helping them with those business outcomes. >>Yeah. It doesn't matter what we do if there isn't that business outcome. >>Yeah. That's what it's all about. I'm curious, Tim, to get your, as the America's cloud leader, one of the things that, that our boss, John Furrier, who is the co CEO of the Cube, was able to do every year, he gets to sit down with the head of AWS for a preview of reinvent, right? He's been doing this for 10 years now, and one of the things that Adam Olitsky said to him, this is something about a week or so ago, is CIOs and CEOs are not coming to me to talk about technology. They wanna talk about transformation. Sure, yeah. Business transformation, not an amorphous topic of digital transformation. Are you hearing the same? >>Absolutely. Right. So I think this is my seventh reinvent, right? And I think six, seven years ago, the majority of the conversations you would've had are about technology, right? Great technology, but kind of technology for it to solve it problems. You know, how do I, how do I migrate, how do I modernize, how do I use data? How do I make all this stuff happen? Right now it's about how do I drive new business opportunities, new revenue streams, how do I drive more efficiencies through the manufacturing 2.0 or what have you, right? Yeah. One really good example, like take, take medical devices, right? So like a connected defibrillator, right? Anytime you're building a, what they call an IOT device or a connected device, right? You have four competing an edge device in the space, an edge device, yeah. Right? You have four competing elements, right? >>You've got form factor, power, connectivity and intelligence, and all those things compete, right? I can have all the power if I want, if I can have something as biggest as a tape, right? You know, I can have satellite if I, it gets right off if I can plug it in somewhere. But when you're talking about an implanted defibrillator, right? That, that all competes. So you have an engineering problem, an engineering challenge that's based on a device, right? And then it's gotta connect to the cloud, right? So you have a lot of AWS services, I ot, core device shadowing, all sorts of things. That individual patient then, so, so there's the engineering challenge of, okay, I wanna build a device, I gotta prototype it, I gotta design it, I gotta build it at scale, I have to support it. Then you have a patient, right? Which is the end goal of the business is the patient care. >>They have a console at home that connects to that defibrillator via Bluetooth, let's say. And that's where you get your device updates, just like your laptop, right? You know, now push from where updates to your chest. Yes. Device, ot. It's like, okay, I'm just gonna do this every Thursday, right? So now you've very quickly move to a patient experience and that patient experience will very greatly, right? You know, based on age and exposure to technology and all other sorts of things, how diligent they are. Do they do the update every week Right. To their primary care provider? And then what we're, we're also hearing, okay, so like Kashmira mentioned, we, we can, we can have that design discussion, right? Yeah. We can have the engineering device discussion with our device, device lab. Then we can have our, you know, what's the, what's the patient experience, but then broader, what's the patient experience as they move, as we all do through a healthcare, that's a healthcare network, it's a provider network, it's a series of hospitals and providers. So what does that big picture and ecosystem look like? And it's, you haven't heard me mention server or data center or any of that stuff? No. Right? This is >>The most human anecdote we've had on >>Show. Fantastic. This >>Sidebar. Okay. I mean it great. Keep going. It's wonderful. And it's, and it's, it's fascinating because none of this happens or is possible without cloud and, and the type of services that AWS is, is releasing out into their, into their, into their, into the world, right? But it very quickly moves from technology to human. It very quickly moves from individual to ecosystem to to, to partner and culture and, you know, society, right? So, so these are the types of conversations we're having. I mean, this is kind of stuff that gets me outta bed in the morning. So it's great, right? It's great that, I love that. It's great that we've moved, we moved into that space. >>Well, it's, I mean the human element is so important. Every, every company has to be a data company. Hospitals, absolutely. Grocery stores, retailers, you name it. And what we're seeing is this, and we talk about data democratization all the time. Well, another thing that Adam Slosky told John Furrier is that the role of, of data analysts is gonna, is going to change, maybe go away or the, or the term because data needs to be everywhere. The doctors need the data. Absolutely. Every person in the organization needs to be able to analyze data to deliver outcomes. >>Yeah, absolutely. Yeah. And it's fundamental part of our strategies. And when we are looking at, you know, data is everywhere, you need to really think about how do you align to it. But we are looking at it from an industry perspective. So when we're looking at solutions for our clients, we're looking at how do we deliver data solutions for our bank? How do we deliver data solutions in healthcare? How do we deliver data solutions in various different industry? So >>Many different verticals that you're >>Touching. Yeah, all the different verticals. So that's, you know, we have like a four point strategy industry is the first one. So we have been really worked with a lot of clients around migrations and modernizations. What we're moving to now is really this industry play. So this week we've spent a lot of time with our energy and utilities clients and the AWS practice at banking and financial services, which is a very significant part of our business. Also cloud automotive. This is a really, really, you know, the fascinat, this is so exciting, but the fundamental part of that, it's very, is data, right? It's all hits on data. So it was really great to hear some of the announcements this week around the data piece announcements just for me, that's really exciting. Yeah. A couple of other things that when we're thinking about our overall focus and strategy is, you know, looking at business transformation is, as you mentioned, is the ecosystem. >>So how do we bring all this together? And it's really, we see ourselves as an ecosystem orchestrator, and we are really here to look at leveraging our relationship with the best partners. We've actually met 17 partners here this week and had client sessions with them. And that's, you know, working with the license of Snowflake and Data Break in the, in the data space, our long term partners like sap, ibm, VMware, and you know, and new partners like Con. And we are looking at how do we bring the best of this ecosystem orchestration so that to support those client business outcome. Sure. And then one final sort of pillar, sorry, is talent, right? So the biggest thing that everyone is thinking about and we all think about every single day is talent. So we've done two really exciting things this year. One has been around our own talent. >>So we've really looked at our own internal influences, people who are speaking to our clients every single day. Not so much the technology people, but the client people speaking to the client. And we've really raised the level of cloud fluency with these people so that they can really start to have that discussion. You know, and our clients, you know, they know this technology way better than us, you most of the time. And then secondly, we actually announced last week and, and you initiative, which we are calling skill skills, which is very well known to our AWS clients because AWS provide this skill, skill concept to their clients. But we are the first partner to do the skills. Skills Yeah. From a partnering perspective. And this is really gonna transform. So it's not just about training and enablement, it's actually about creating a journey for you to, you know, do your best work. >>Tim, what, how do you define cloud fluency? We were actually talking about it yesterday. Sure, sure. Yeah. And, and really kind of bringing that across an organization, but what, what does it take for an individual who may not be a technologist to become cloud fluent? >>Sure. Well, there's a couple, there's a couple angles to that, right? One is, one is how do you create cloud fluency for people who might already be technical, right? And that's, and that's, you know, I've spent over a decade with, you know, boutique disruptive consulting companies who live and die by whether they can attract and retain talent. And there's sort of four elements to that. It's, can you, can you show people they're gonna work on interesting stuff, right? Are they gonna be excited about what they do? Can you show that they're gonna expand their skill sets? Yep. Can you show them a career path? And you can, can you surround all of that with a supportive engineering first culture, right? That, you know, rewards for outcomes, but also creates this sort of community, right? Yeah. That's, that's one thing that sort of, you know, that that will be a natural entropy, people will be attracted to that. On the other side of it, as you create fluency, you kind of do it with the conversation that I just had, like around something like medical devices or something like the cloud car. When you just say, look, you start with something everybody already knows, right? We all know what patient care is like. We all know what autonomous vehicles is kind of like, right? And you work backwards from that and say, now here's, here's how all the pieces stitch together to create this end outcome for, for us and for our customers, for >>The, you know, I'm speaking my language, Tim. So I run a boutique consultancy, my talent go, I live and die on that. Quite frankly. It's everything, right? And, and it's so, wow, it's so important. I mean, in eliminating that churn at scale, how big is your team? Now I'm just thinking about this cause I'm sure you're, your talent retention has to be a challenge as well. Sure. >>So, so we have 25,000 woo professionals on aws trained on, you know, tech cloud technologies globally. Impressive. Yeah. And then we have, in terms of our go to market team, we've got 50 strong as well. Well, so we, these are people who are live and breathe aws, right? And speaking and working with the cloud. >>Let's hang out there a little bit. Tell us a little bit more about the partnership with aws. Cast me, >>Let's go to you. Yeah, so our partnership is, you know, it's 11 years strong. It's been an and a really, really great partnership's. >>How longs >>That's true. Yeah. >>No, is you, were, you're, you're like day ones there. That's Yeah. Real legacy it. >>Awesome. You know, this year excitingly, we actually won the APJ partner of dsi, partner of the year. Congratulations. >>Really casual. >>Yeah. Just like >>Married the lead there. Congratulations. >>Yeah. So that really is testament to how we're really knuckling down and working proactively to, to really support our clients. And, you know, the, the partnership is a really, really strong partnership. It's been there for many years with, you know, great solutions and engagement and many of the things I talked about in terms of our industry plays that we're driving. We've got a whole new set of competencies that we've launched, like a new energy competency this year. So we're focusing on industry and then also security, two new security competencies. And you know, what's really exciting on the security side, you saw the announcements around the security data lake, but we've been working over the last few months with Gary, me and his team, and actually are one of the first partners that are driving that initiative. So we're really proud to be part of that. So yeah. You know, and then there's a client engagement as well. So we have a dedicated team at AWS that works with our dedicated team. So we're supporting the client's needs day to day. >>Are you as customer obsessed as AWS is? Absolutely. I >>Figured so. Absolutely. Everything's about the customer. Nothing happens about >>That. Right? Well, you talked about outcomes, it's all about outcomes. >>Well, and I mean, quite literally going for the heart with the defibrillator analogy. No, I mean, you tell the customers at the heart of what you're doing, part of everything. Can't resist a good pun there. So as I warned you, we have a little challenge for you here on the cube. We're looking for your hot take your 32nd sound bite thought leadership. What's the biggest takeaway from the event and moving forward, looking into 2023? Tim, you're giving me that eye contact. I'm going to you first, >>Right? Okay, sure. Love to. So I don't know how hot a take it is, but I kind of see this transition as cloud, as the operating system, right? So, so let's take the, the what we call the cloud car project. We have the connected car. You know, a car is a durable good, and we all know, or there's been a lot of talk about the electric cars or the autonomous vehicles being like more of a computer than a vehicle, right? But a vehicle's supposed to last 10, 15, 20 years. Our laptops don't last 10, 15, 20 years. So there's this cell, there's this major challenge to say, how can I, how can I change the way the technology operates within the vehicle? So you see this transition to where instead of it being a car that, that has a computer, then it, the, the, the latest transition is to more of a computer that, that operates like a car. >>This new vehicle that's going to emerge is gonna be much like a cell phone, right? Where it, it traverses the world and depending on where it is, different things might be available, right? And, and how and how, how the actual technology, the software that is running will, will be, you know, sort of amorphous and move between different resources in the network on the car, everywhere else. And so that's a really different way of thinking about if, if we think about how quickly the Overton window, like what becomes normal, it changes over time. We're really getting to like a very fast movement of that into something like this vehicle's still gonna be something that we don't even maybe think of as a car anymore. Just the way that an iPhone isn't what we used to think of a phone at our >>Pocket computer. Yeah. What's in the mirror part? Great. >>That's kind my >>Take. Awesome. Right? Catch me man. >>Yeah, and I mean I, if I was to suggest that, you know, summarize it by simply, for me it's really focusing on industry solutions, delivering client outcomes, fundamentally underpinned by data security and sustainability. You know, I think Nailed it. >>Yeah. Knock it outta the park. Perfect little sound bite. That was fantastic. You both were a wonderful start to the day. Thank you so much for being here. Tim and Kashmir, absolute >>Pleasure. >>This is, this is a joy. We're gonna keep learning here on the cube. And thank all of you for tuning in to our fabulous AWS reinvent coverage here from Sin City with Lisa Martin. I'm Savannah Peterson and you are watching The Cube, the leader in high tech coverage.

>>Hey everyone. Welcome back to Chicago. Lisa Martin here with John Furrier. We're live with the Cube at Ansible Fest 2022. This is not only Ansible's 10th anniversary, John Wood. It's the first in-person event in three years. About 14 to 1500 people here talking about the evolution of automation, really the democratization opportunities. Ansible >>Is money, and this segment's gonna be great. Cub alumni are back, and we're gonna get an industry perspective on the automation journey. So it should be great. >>It will be great. We've got two alumni back for the price of wine. Scott Canine joins us, Director of Worldwide Automation at Kendra. A Nelson Shoe is back as well. Product marketing director at Red Hat. Guys, great to have you back on the, on the live cube. >>Oh, thank you for having us. And, and you know, it's really great to be back here live and in person and, and, you know, get a chance to see you guys again. >>Well, and also you get, you get such a sense of the actual Ansible community here. Yeah. And, and only a fraction of them that are here, but people are ready to be back. They're ready to collaborate in person. And I always can imagine the amount of innovation that happens at these events, just like off the show floor, people bumping into each other and go, Hey, I had this idea. What do you think, Scott? It's been just about a, a year since Kenel was formed. Talk to us about the last close to a year and what that's been like. Especially as the world has been so, chops >>The world been Yeah, exactly. Topsy turvy. People getting back to working in person and, and everything else. But, you know, you know, throw on that what we've done in the last year, taking Kendra, you know, outside of being a part of ibm Right. In our own company at this point, you know, and you know, you hear a lot of our executives and a lot of our people when we talk about it, like, Oh yeah, it's, you know, it's a $19 billion startup. We got freedom of action. We can do all these different things. But, you know, one of the ways I look at it is we are a $19 billion startup, which means we've got a lot of companies out there that are trusting us to, no matter what change we're doing, continue to deliver their operations, do it flawlessly, do it in a way so they can continue to, to service their clients effectively and, and don't break 'em. And, and so that to me, you know, the way we do that and the way I focusing on that is automation Ansible, obviously corridor strategy, getting there. >>Yeah. And I'd like to get your thoughts too, because we seeing a trend, we've been reporting on this with the cloud growth and the scale of cloud and distributed computing going cloud native, the automation is the front and piece center of all conversations. Automate this, make developers go faster. And with the pandemic, we're coming out of that pandemic. You post pandemic with large scale automation, system architecture, a lot more like architectural conversations and customers leaning on new things. Yeah. What are you seeing in this automation framework that you guys are talking about? What's been the hot playbook or recipe or, or architecture to, you know, play on words there, but I mean, this is kind of the, the key focus. >>Yeah. I mean, if you, one of the things that I com customer comp talks, I've been pulled into a lot recently, have all been around thinking about security, right? A lot in terms of security and compli, I think, I mean, think about the world environment as a whole, right here, everything that's been going on. So, so people are, are conscious of how much energy that's being used in their data centers, right? And people are conscious of how secure they are, right? Are they, you know, the, their end customers are trusting them with data information about them, right? And, and they're trusting us to make sure that those systems are secure to make sure that, you know, all that is taken care of in the right way. And so, you know that what's hot security and compliance, right? What can we do in the energy space, right? Can we do things to, to help clients understand better their energy consumption as, as, you know, especially as we get now in Europe to the winter months, can we do things there that'll help them also be better in that space, Right? Reduce their >>Costs and a lot more cloud rails obviously right there. You got closer and you got now Ansible, they're kind of there to help the customers put it together at scale. This has been the big conversation last year, remember was automate, automate, automate, right? This year it's automation everywhere, in every piece of the, the landscape edge. It's been big discussion tomorrow here about event driven stuff. This is kind of a change of focus and scope. Can you like, share your thoughts on how you see how big this is in terms of the, the, the customer journey >>In terms, I'm sorry, in terms of, >>In terms of their architecture, how they're rolling out automation, >>What's their Yeah, yeah. So, so in terms of their rolling out arch, arch in terms of them consuming architecture, right? And the architecture or consuming automation. Yeah. And rolling out the architecture for how they do that. You know, again, it, to me it's, it's a lot of, it's been focused around how do we do this in the most secure manner possible? How do we deliver the service to them and the most secure managers possible? How do they understand that it, that they can trust the automation and it's doing the right things on their environments, right? So it's not, you know, we're not pushing out or, or you know, it's not making bad policies >>And they're leaning on you guys. >>It's, it's not being putting malware out there, right? At the same time we're doing different things. And so they really rely on, on our customers, rely on us to really help them with that journey. >>I think a, a big part of that with Kendra as such a great partner and so many customers trusting them, is the fact that they really understand that enterprise. And so as, as Scott talks about the security aspect, we're not just talking to the IT operations people, right? We're talking across the enterprise, the security, the infrastructure, and the automation around that. So when we talk about hybrid cloud, we talk about network and security edge is a natural conversation to that, cuz absolutely at the edge network and security automation is critical. Otherwise, how are you gonna manage just the size of your edge as it grows? >>Yeah. And, and we've been, and that's another area that we've been having a a lot more conversations with clients on, is how do you do automation for IOT and edge based devices, right? We, you know, traditionally data center cloud, right? Kind of the core pieces of where we've been focusing on, but I, you know, recently I've been seeing a lot more opportunities and a lot more companies coming forward saying, you know, help us with the network space, help us with the iot space. We really wanna start getting to that level of automation and that part of our environments. And what >>Are some of the key barriers that customers are coming to you with saying, help us overcome these so that they can, you're smiling so that they can, can obviously attract and retain the right talent and also be able to determine what processes to automate to extract the most value and the most ROI for the organization. >>Yeah. And, and, and you know, that's, that's an interesting, the ROI conversation's always an interesting one, right? Because when you start having that with customers, some of the first things they think about, or the first, the natural place people go is, >>Oh, >>Labor takeout. I can do this with less people. Right? But that's not the end all be all of automation. In fact, you know, my personal view is that's, you know, maybe the, the the bottom 30%, right? That's kind of, then you have to think about the value you get above and beyond that standard operations, standardized processes, right? How are you gonna able to do those faster? How's that enabling your business, right? What's all the risks that's now been taken out by having these changes codified, right? By having them done in a manner that is repeatable, scalable, and, and, and really gets them to the point of, you know, what their business needs from an operational standpoint and >>Extracting that value. Nelson, talk about the automation journey from your perspective, How have you seen that evolve from your lens, especially over the last couple of years? >>It's a great question. You know, it's interesting because obviously all of our customers are at different stages of their automation journey. We have someone that just beginning looking at automation, they've been doing old scripts, if you will, the past. And then we have more that are embracing it, right? As a culture. So we have customers that are building cultures of automation, right? They have standups, they have automation guilds. It's, it's kind of a little bit of a, of a click. It's kind of, you know, building up steam in that momentum. And then we have, you know, the clients that Kindra works with, right? And they're very much focused on automation because they understand that they have a lack of resources, they don't have the expertise, they don't have the time to be able to deliver all this. Yeah. And that's really, Kendra really comes into effect to really help those customers accelerate their automation. Yeah. Right. And to that point, you know, we're doing a lot of innovation work with Kendra and we lean on them heavily because, you know, they're willing to make that commitment as a partner both on the, the, the day to day work that we do together as well as Ford looking at different architectures. >>Yeah. And, and the community aspect from our side internally has been tremendous in terms of us being able to expand what we'll be doing with automation and, and what a's been able to do with that community to get there. Right? Yeah. So to last month we did about 33 million day one, day two operations through automation, right? So that's what we've done. If you look at it, you know, if I break it down, it's really 80% of that standard global process stuff that we bring to the table. 20% of that is what our, our account teams are bringing specifically to their clients based on their needs and what they need to get done. Right. You know, one of my favorite examples of of, of this, right? We have a automation example out there for a, a client we've got in Japan, right? They tie, you know, they're, they're obviously concerned, you know, security a everything else that we've been talking about. >>They're also concerned about resiliency, right? In the face of natural disasters. Yeah. So they took our automation, they said, Okay, we're gonna tie your platform to seismic data that's coming through, and we understand what seismic data's happening. Okay, it's hitting a certain event. Let's automatically start kicking off resiliency operations so we can be prepared and thus keeps serving our clients when that's happening. Right? And that's not something like when you talk about a global team coming in and, and saying, we're gonna do all this. It's that community aspect, getting, getting the account focus, getting to that level, right? That's really brings value to clients. And that's one of the use cases, you know, and aaps enabled us to do with the a the community approach. We've got >>Now talk about this partnership. I think earlier when we were talking to Stephanie and Tom, the bottoms up Ansible community with top down kind of business objectives kind of come into play. You guys have a partnership where it's, there's some game changing things happening because Ansible's growing, continuing to have that scope grow from a skill set standpoint, expand the horizons, doing more automation at scale, and then you got business objectives where people wanna move faster in their, in their digital transformation. So to me, it's interesting that this part kind of hits both. >>It does really hit both. I mean, you know, the community cloud that Kendra has is so critical, right? Because they build that c i CF architecture internally, but they follow that community mantra, if you will. And community is so important to us, right? And that's really where we find innovation. So together with what we were call discussing about validated content earlier today becomes critical to build that content to really help people get started, Right? Validated content, content they can depend on and deliver, right? So that becomes critical on the other side, as you mentioned, is the reality of how do we get this done? Yeah. Right? How do we mature, how do we accelerate? And without the ability to drive those solutions to them to fix, if you are the problems that the line of business has. Well, if you don't answer those questions with the innovation, with the community, and then with the ap, it's, it, it does, it's gotta all come >>Together as, I mean, that community framework is interesting. I think we hear a lot in the cube, you know, Hey, let's do this. Sounds good. Who's gonna do it? Someone who's the operator. So there's a little skills gap going on. It's also a transformation in the roles of the operators in particular, and the dev, So the DevOps equation's completely going to the next level, right? And this is where people wanna move faster. So you're seeing a lot more managed services, a lot more Yes. Services that's, I won't say so much top down, but more like, let's do it and here's a play to get it done, right? Then backfill on the hiring, whether it's taking on a little bit of technical debt or going a little faster to get the proof points, >>Right? And I think one of the critical aspects is, you know, Ansible has it certified collections, right? And oftentimes we, we don't, I don't, I meet with customers two, three times a week, right? There's not a single one that doesn't emphasize the importance of partners and the importance of certified collections, Right? And kindra is included in that, right? Because they bring a lot of those certified collections. Use them, leverage them, it's helps customers get a jumpstarter, right? It's a few, it's their easy button, right? But they only get that and they value that because of the support that's there. >>Yeah. Right? They get the with >>The cert. Yeah. I was gonna say, just adding on the certified collections, right? We, so, you know, it was, it was great to see the hub come out with those capabilities because, you know, as we've gone through the last 12 months and, and change, one of the things that we focused more in on is network devices, network support, right? And, and so, you know, some of the certified collections out there for Cisco for F five, right? Some of those things we've been able to take back in and now build on top of with the expertise that we, we have in that space as well. And then use that as a starting point to more value for our clients. >>How is Kentrell working together with, with Red Hat and with Ansible to help organizations like you mentioned Nelson, they're on the journey varies considerably. Some are well on their way, others aren't. But for those to really start developing an automation, first culture, we talked a lot about cultural ship, we talked about it this morning. You can feel the power of that community and driving it, but how do you guys work together to help companies and any industry kind of really start understanding what an automation first culture is and then building it internally and getting some grounds? Well, >>Well, it's interesting, right? One of the, one of the things that really is we found really helpful is assessments, right? So you have silos and pockets of automation, and that's that challenge, right? So to be able to bring that, if you are automation community within an enterprise together, we often go out and we'll do an assessment, right? An automation assessment to really understand holistically how the enterprise could leverage automation not just in the pockets, but to bring it together. And when they bring that automation together, they can share, playbooks can share their experiences, right? And with Kindra and the multiple and the practices they have, right? They really bring that home from an industry perspective. They also bring that home, if you will, from a technology perspective. And they bring that together. So, you know, Kindra in that respect is the glue for our customer success. >>What's news? What's the next big thing that you guys see? Because if this continues down the road, this path, people are gonna get, the winds gonna get the successes. The new beachhead, if you will, is established. You got the edge around the corner. What's next for you guys in the partnership? How do you see it developing? >>No, we're looking at >>No, it's all good. So really, you know, I, I mentioned it earlier and, and the jour the automation journey paralleled by innovation, right? Customers today are automating, they're doing a great job. There's multiple tools out there. We understand we're not gonna be the only tool in the shed, but Ansible can come in and integrate that entire environment. And in a hybrid cloud environment, you want that there, right? I think what next is obviously the hybrid cloud is critical. The edge is critical, right? And I think that, you know, the needs and the requirements that Kindra hears that we have is kind of that future. And, you know, we, we often, often in, in Red Hat, we talk about a north star, right? And when I work with partners, ikin, do we talk about the North Star, where we want to get to? And that is the acceleration of automation. And I think both by the practical aspect of working with our customers and the innovation as partners, as business partners, technology partners will help accelerate >>That. Yeah. Scott, your perspective to bridge to the future is obviously hybrid and edge, how you bringing your customers along? >>Yes. So, so we see, you know, when we talk about my, when I talk about my automation strategy, our automated strategy, right? It's about being automated, orchestrated and intelligent, right? Kind of those, those three layers of the stack. We've been building out a lot of work, what we call our integrated AIOps layer for actionable insights, right? We've got a, you know, a goal to integrate that and, and we have integrated into our automation service for how we're delivering the whole package to our clients so they can better see opportunities for automation. What's the best way to go about it? You know, what are the, what are some of the, the issues they have, vulnerabilities they have in their environment and really bringing it to them in, in a real holistic manner. In fact, we internally, we call it our F five steering wheel, right? Based on the, the race thing, right? >>Because you think about the, the racing cars, f fives know they're right there, right? They got everything they need in front of 'em. Yeah. So our goal is been to, to include that into our automation view and service and build that out, right? So that's one way we're doing it. The additional way is, is through some announcements you probably heard, hopefully heard the last couple weeks through something called Kendra Bridge, right? Kendra Bridge is more the digitization of, of the way we deliver services for our clients to make it easier for them to consume and, and to, to make the barrier to entry for things like getting automation, getting it more in their environment, right? Lower as much as possible, right? So really integrated AIOps kind bridge. Those are really the two ways we see it as, as going forward. >>It's interesting, you know, we live through a lot of these different inflection points in the industry. Every time there's a big inflection point, there's more complexity that needs to be tamed, you know? And so you got innovation. If you got innovation coming and you got the clients wanna simplify and tame the complexity, this is a big part of what you guys do. >>Absolutely. Yeah. I mean, how do we, you know, most, when the clients come to us, right? Like I said, one, it's about trust. They trust us to do it because we can make it easy for them to not have to worry about that, right? Yeah. They don't have to worry about what it takes to secure the environment, manage it, run it, design it, build it for the, the cloud. We give 'em the ability, we give them the ability to focus on their core business while we do the stuff that's important to them, which >>Is absolutely critical that you, you can't emphasize trust in this relationship enough. I wish we had more time, guys, you're gonna have to come back. I think that's basically what this is boil down to. But thanks so much guys for talking with John and me about how Kendra and and Ansible are working together, really enabling your customers to, to unlock the value of automation across their organization and really make some big business changes. We appreciate your insights and your time. Fantastic. Thank you. Happy to do it and happy to do it any time. All right. Our pleasure. Thank you so much for our guests and John Furrier. I'm Lisa Martin. You're watching The Cube Live from Chicago. This is day one of our coverage of Ansible Fest 22. Don't go anywhere. Our next guest joins us in just a minute.

>>Okay, we're back with Jen Vera, who's the Chief Human Resource Officer of Dell, and we're gonna discuss people, culture and hybrid work and leadership in the post isolation economy. Jen, the conversations that we had at Dell Tech World this past May around the new work environment were some of the most interesting and engaging that I had personally. So I'm really eager to, to get the update. It's great to see you again. Thanks for coming on the cube. >>Thanks for having me, Dave. There's been a lot of change, just a short amount of time, so I'm excited to, to share some of our learnings with >>You. I, I mean, I'll bet there has, I mean, post pandemic companies, they're trying, everybody's trying to figure out the return to work and, and what it looks like. You know, last May there was really a theme of flexibility, but depending, we talked about, well, millennial or not young old, and it's just really was mixed, but, so how have you approached the topic? What, what are your policies? What's changed since we last talked? You know, what's working, you know, what's still being worked? What would you recommend to other companies to over to you? >>Yeah. Well, you know, this isn't a topic that's necessarily new to Dell technology. So we've been doing hybrid before. Hybrid was a thing, so for over a decade we've been doing what we called connected workplace. So we have kind of a, a history and we have some great learnings from that. Although things did change for the entire world. You know, March of 2020, we went from kind of this hybrid to everybody being remote for a while. But what we wanted to do is, we're such a data driven company. There's so many headlines out there, you know, about all these things that people think could happen will happen, but there wasn't a lot of data behind it. So we took a step back and we asked our team members, How do you think we're doing? And we asked very kind of strong language, because we've been doing this for a while. >>We asked them, Do you think we're leading in the world of hybrid? And 86% of our team members said that were, which is great, but we always know there's nuance right behind that macro level. So we, we asked them a lot of different questions and we just went on this kind of myth busting journey and we decided to test some of those things. We're hearing about Culture Willow Road or new team members will have trouble being connected or millennials will be different. And we really just collected a lot of data, asked our team members what their experiences. And what we have found is really, you don't have to be together in the office all the time to have a strong culture, a sense of connection, to be productive and to have a really healthy business. >>Well, I like that you were data driven around it with the data business here. So, but, but there is a lot of debate around your culture and how it suffers in a hybrid environment and how remote workers won't get, you know, promoted. And so I'm curious, you know, and I've, and I've seen some like-minded companies like Dell say, Hey, we want you guys to work the way you wanna work. But then they've, I've seen them adjust and say, Well, yeah, but we also want you to know in the office, be so we can collaborate a little bit more. So what are you seeing at Dell and, and, and how do you maintain that cultural advantage that you're alluding to in this kind of strange, new ever changing world? >>Yeah. Well, I think, look, one approach doesn't fit all. So I don't think that the approach that works for Dell Technologies is necessarily the approach that works for every company. It works with our strategy and culture. It is really important that we listen to our team members and that we support them through this journey. You know, they tell us time and time again, one of the most special things about our culture is that we provide flexibility and choice. So we're not a mandate culture. We really want to make sure that our team members know that we want them to be their best and do their best. And not every individual role has the same requirements. Not every individual person has the same needs. And so we really wanna meet them where they are so that they can be productive. They feel connected to the team and to the company and engaged and inspired. >>So, you know, for, for us, it really does make sense to go forward with this. And so we haven't, we haven't taken a step back. We've been doing hybrid, We'll continue to do hybrid, but just like if you, you know, we talk about not being a mandate. I think the companies that say nobody will come in or you have to come in three days a week, all of that feels more limiting. And so what we really say is, work out with your team, work out with your role work, workout with your leader, what really makes the most sense to drive things forward. >>I, >>You were, were talking, that's >>What we, you were talking before about myths and you know, the, I wanna talk about team member performance cuz there's a lot of people believe that if, if you're not in the office, you have disadvantages, People in the office have the advantage cuz they get FaceTime. Is is that a myth? You know, is there some truth to that? What, what do you think about that? >>Well, for us, you know, we look, again, we just looked at the data. So we said we don't wanna create a have and have not culture that you're talking about. We really wanna have an inclusive culture. We wanna be outcome driven, we're meritocracy. But we went and we looked at the data. So pre pandemic, we looked at things like performance. We looked at rewards and recognition, we looked at attrition rates, we looked at sentiment, Do you feel like your leader is inspiring? And we found no meaningful differences in any of that or in engagement between those who worked fully remote, fully in the office or some combination between. So our data would bust that myth and say, it doesn't, you don't have to be in an office and be seen to get ahead. We have equitable opportunity. Now, having said that, you always have to be watching that data. And that's something that we'll continue to do and make sure that we are creating equal opportunity regardless of where >>You work. And it's personal too, I think, I think some people can be really productive at home. I happen to be one that I'm way more productive in the office cause the dogs aren't barking. I have less distractions. And so, yeah, I think we think, and I think the takeaway that in just in talking to, to, to you Jen and, and folks at Dell is, you know, whatever works for you, we're we're gonna, we're gonna support. So I, I wanted to switch gears a little bit and talk about leadership and, and very specifically empathic leadership has been said to be, have a big impact on attracting talent, retaining talent, but, but it's hard to have empathy sometimes. And I know I saw some stats in a recent Dell study. It was like two thirds the people felt like their organization underestimates the people requirements. And I, I ask myself, I'm like, Hmm, what am I missing? You know, with our folks. So especially as it relates to, to transformation programs. So how can human resource practitioners support business leaders generally, specifically as it relates to leading with empathy? >>I think empathy's always been important. You have to develop trust. You can have the best strategy in the world, right? But if you don't feel like your leader understands who you are, appreciates the the value that you bring to the company, then you're not gonna get very far. So I think empathetic leadership has always been part of the foundation of a trusting, strong relationship between a leader and a team member. But if I think we look back on the last two years, and I imagine it'll be even more so as we go forward, empathetic leadership will be even more important. There's so much going on in the world, politically, socially, economically, that taking that time to say you want your team members to see you as credible, that you and confident that you can take us forward, but also that, you know, and understand me as a human being. >>And that to me is really what it's about. And I think with regard to transformation that you brought up, I think one of the things we forget about as leaders, we've probably been thinking about a decision or a transformation for months or weeks and we're ready to go execute, We're ready to go operationalize that thing. And so sometimes when we get to that point, because we've been talking about it for so long, we sent out the email, we have the all hands and we just say we're ready to go. But our team members haven't always been on that journey for those months that we have. And so I think that empathetic moment to say, Okay, not everybody is on this change curve where I am. Let's take a pause, let me put myself in their shoes and really think about how we bring everybody along. Culture. >>You know, Jen, in the spirit of myth busting, I mean I'm one of those people who felt like that a business is gonna have a hard time, harder time fostering this culture of collaboration and innovation in post isolation economy as they, they could pre covid. But you know, I notice there's, there's an announcement today that came across my desk, I think it's from Newsweek. Yes. And, and it's the list of top hundred companies recognized for employee motivation satisfaction. And it was really interesting because you, you always see, oh, we're the top 10 or the top hundred, But this says as a survey of 1.4 million employees from companies ranging from 50 to 10,000 employees. And it recognizes the companies that put respect, caring, and appreciation for their employees at the center of their business model and doing so have earned the loyalty and respect of the people who work for them. >>Number one of the lists is Dell sap. So congratulations. SAP was number two. I mean, there really isn't any other tech company on there, certainly no large tech companies on there. So I always see these lists, they go, Yeah, okay, that's cool. Top a hundred, whatever. But top one in, in, in an industry where there's only two in the top is, is pretty impressive. And how does that relate to fostering my earlier skepticism of a culture of collaboration? So first of all, congratulations, you know, how'd you do it and how are you succeeding in, in this new world? >>Well thanks. It does feel great to be number one, but you know, it doesn't happen by accident. And I think while most companies have a, a culture and a spouse values, we have ours called the culture code. But it's really been very important to us that it's not just a poster on the wall or or words on paper. And so we embed our culture code into all of our HR practices, that whole ecosystem from recognition rewards to performance evaluation, to interviewee to development. We build it into everything. So it really reflects who we are and you experience it every day. And then to make sure that we're not, you know, fooling ourselves, we ask all of our employees, do you feel like the behaviors you see and the experience you have every day reflects the culture code? And 94% of our team members say that, in fact it does. So I think that that's really been kind of the secret to our success. If you, if you listen to Michael Dell, he'll always say, you know, the most special thing about Dell is our culture and our people. And that comes through being very thoughtful and deliberate to preserve and protect and continue to focus on our culture. >>Don't you think too that repetition and, well first of all, belief in that cultural philosophy is, is important and then kind of repeating, like you said, Yeah, it's not just a poster on the wall, but I remember like, you know, when we're kids, your parents tell you, okay, power a positive thinking, do want to others as others, you know, you have others do it to you. Don't make the see you're gonna do some dumb things but don't do the same dumb things twice and you sort of fluff it up. But then as you mature you say, Wow, actually those were, >>That you might have had a >>Were instilled in me and now I'm bringing them forward and you know, paying it forward. But, but so it, my, I guess my, my point is, and it's kind of a point observation, but I'll turn it into a question, is isn't isn't consistency and belief in your values really, really important? >>I couldn't agree with you more, right? I think that's one of those things that we talk about it all the time and as an HR professional, you know, it's not the HR people just talking about our culture, it's our business leaders, it's our ceo, it's our CEOs, it's our partners. We share our culture code with our partners and our vendors and our suppliers and, and everybody, this is important. We say when you interact with anybody at Dell Technologies, you should expect that this is the experience that you're gonna get. And so it is something that we talk about that we embed in, into everything that we do. And I think it's, it's really important that you don't just think it's a one and done cuz that's not how things really, really work >>Well. It's a culture of respect. You know, high performance, high expectations, accountability, having followed the company and worked with the company for many, many years, you always respect the dignity of your partners and your people. So really appreciate your time Jen. Again, congratulations on being number one. >>Thank you so much. >>You're very welcome. Okay. You've been watching a special presentation of the Cube inside Dell Technology Summit 2022. Remember, these episodes are all available on demand@thecube.net and you can check out silicon angle.com for all the news and analysis. And don't forget to check out wikibon.com each week for a new episode of breaking analysis. This is Dave Ante, thanks for watching and we'll see you next time.

>>As we said in our analysis of Dell's future, the transformation of Dell into Dell emc and now Dell Technologies has been one of the most remarkable stories in the history of the technology industry. After years of successfully integrated EMC and becoming VMware's number one distribution channel, the metamorphosis of Dell com culminated in the spin out of VMware from Dell and a massive wealth creation milestone pending, of course the Broadcom acquisition of VMware. So where's that leave Dell and what does the future look like for this technology powerhouse? Hello and welcome to the Cube's exclusive coverage of Dell Technology Summit 2022. My name is Dave Ante and I'll be hosting the program today In conjunction with the Dell Tech Summit. We'll hear from four of Dell's senior executives. Tom Sweet is the CFO of Dell Technologies. He's gonna share his views of the company's position and opportunities and answer the question, why is Dell good long term investment? >>Then we'll hear from Jeff Boudreau was the president of Dell's ISG business unit. He's gonna talk about the product angle and specifically how Dell is thinking about solving the multi-cloud challenge. And then Sam Grow Cot is the senior vice president of marketing's gonna come in the program and give us the update on Apex, which is Dell's as a service offering and a new edge platform called Project Frontier. By the way, it's also Cybersecurity Awareness Month, and we're gonna see if Sam has any stories there. And finally, for a company that's nearly 40 years old, Dell has some pretty forward thinking philosophies when it comes to its culture and workforce. And we're gonna speak with Jen Savira, who's Dell's chief Human Resource officer about hybrid work and how Dell is thinking about the future of work. We're gonna geek out all day and talk multi-cloud and edge and latency, but first, let's talk wallet. Tom Sweet cfo, and one of Dell's key business architects. Welcome back to the cube, >>Dave, it's good to see you and good to be back with you. So thanks for having me, Jay. >>Yeah, you bet. Tom. It's been a pretty incredible past 18 months. Not only the pandemic and all that craziness, but the VMware spin, you had to give up your gross margin binky as kidding, and, and of course the macro environment. I'm so sick of talking about the macro, but putting that aside for a moment, what's really remarkable is that for a company at your size, you've had some success at the top line, which I think surprised a lot of people. What are your reflections on the last 18 to 24 months? >>Well, Dave, it's been an incredible, not only last 18 months, but the whole transformation journey. If you think all the way back maybe to the LBO and forward from there, but, you know, stepping into the last 18 months, it's, you know, I, I think I remember talking with you and saying, Hey, you know, this scenario planning we did at the beginning of this pandemic journey was, you know, 30 different scenarios roughly, and none of which sort of panned out the way it actually did, which was a pretty incredible growth story as we think about how we helped customers, you know, drive workforce productivity, enabled their business model during the all remote work environment. That was the pandemic created. And couple that with the, you know, the, the rise then and the infrastructure spin as we got towards the tail end of the, of the pandemic coupled with, you know, the spin out of VMware, which culminated last November, as you know, as we completed that, which unlocked a pathway back to investment grade within unlocked, quite frankly shareholder value, capital allocation frameworks. It's really been a remarkable, you know, 18, 24 months. It's, it's never dull at Dell Technologies. Lemme put it that way. >>Well, well, I was impressed with you, Tom, before the leverage buyout and then what I've seen you guys navigate through is, is, is truly amazing. Well, let's talk about the challenging macro. I mean, I've been through a lot of downturns, but I've never seen anything quite like this with fed tightening and you're combating inflation, you got this recession looming, there's a bear market you got, but you got zero unemployment, you're rising wages, strong dollar, and it's very confusing. But it spending is, you know, it's somewhat softer, but it's still not bad. How are you seeing customers behave? How is Dell responding? >>Yeah, look, if you think about the markets we play in Dave, and we should start there as a grounding, you know, the, the total market, the core market that we think about is roughly 700 and, you know, 50 billion or so. If you think about our core IT services capability, you couple that with some of the, the growth initiatives that we're driving and the adjacent markets that that, that brings in, you're roughly talking a 1.4 to $1.5 trillion market opportunity, total addressable market. And so from from that perspective, we're extraordinarily bullish on where are we in the journey as we continue to grow and expand. You know, we have, we're number one share in just about every category that we plan, but yet when you look at that, you know, number one share in some of these, you know, our highest share position may be, you know, low thirties and maybe in the high end of storage you're at the upper end of thirties or 40%. >>But the opportunity there to continue to expand the core and, and continue to take share and outperform the market is truly extraordinary. So, so you step back and think about that, then you say, okay, what have we seen over the last number of months and quarters? It's been, you know, really great performance through the pandemic as, as you highlighted, we actually had a really strong first half of the year of our fiscal year 23 with revenue up 12% operating income up 12% for the first half. You know, what we talked about as you, if you might recall in our second quarter earnings, was the fact that we were starting to see softness. We had seen it in the consumer PC space, which is not a big area of focus for us in the sense of our, our total revenue stream, but we started to see commercial PC soften and we were starting to see server demand soften a bit and storage demand was, was holding quite frankly. >>And so we gave a a framework around guidance for the rest of the year as a, of what we were seeing. You know, the macro environment as you highlight it continues to be challenging. You know, if you look at inflation rates and the efforts by central banks across the globe to with through interest rate rise to press down and, and constrain growth and push down inflation, you couple that with supply chain challenges that continue principle, particularly in the ISG space. And then you couple that with the Ukraine war and the, and the energy crisis that that's created. And particularly in Europe, it's a pretty dynamic environment. And, but I'm confident, you know, I'm confident in the long term, but I do think that there is, you know, that there's navigation that we're going to have to do over the coming number of quarters, who knows quite how long, you know, to, to make sure the business is properly positioned and, you know, we've got a great portfolio and you're gonna talk to some of the team LA later on as you think your way through some of the solution capabilities we're driving what we're seeing around technology trends. >>So the opportunities there, there's some short term navigation that we're gonna need to do just to make sure that we address some of the, you know, some of the environmental things that we're seeing right >>Now. Yeah. And as a global company, of course you're converting local currencies back to appreciated dollars. That's, that's, that's another headwind. But as you say, I mean, that's math and you're navigating it. And again, I've seen a lot of downturns, but you know, the best companies not only weather the storm, but they invest in ways they that allow them to cut out, come out the other side stronger. So I wanna talk about that longer term opportunity, the relationship between the core, the the business growth. You mentioned the tam, I mean, even as a lower margin business, if, if you can penetrate that big of a tam, you could still throw off a lot of cash and you've got other levers to turn in potentially acquisitions and software. And, but so ultimately what gives you confidence in Dell's future? How should we think about Dell's future? >>Yeah, look, I, I think it comes down to we are extraordinarily excited about the opportunity over the long term digital transformation continues. I I am on numerous customer and CIO calls every week. Customers are continuing to invest in digital transformation and infrastructure to enable their business model. Yes, maybe it's gonna slow or, or pause or maybe they're not gonna invest quite at the same rate over the next number of quarters, but over the long term the needs are there. You look at what we're doing around the, the growth opportunities that we see, not only in our core space where we continue to invest, but also in the, what we call the strategic adjacencies. Things like 5G and modern telecom infrastructure as our, the telecom providers across the globe open up their, what a cl previous been closed ecosystems, you know, to open architecture. You think about, you know, what we're doing around the edge and the distribution now that we're seeing of compute and storage back to the edge given data gravity and latency matters. >>And so we're pretty bullish on the opportunity in front of us, you know, yes, we will and we're continuing to invest and you know, Jeff Boudreau talk about that I think later on in the program. So I'm excited about the opportunities and you look at our cash flow generation capability, you know, we are in, in, in normal times a, a cash flow generation machine and we'll continue to do so, You know, we've got a negative, you know, CCC in terms of, you know, how do we think about efficiency of working capital? And we look at our, you know, our capital allocation strategy, which has now returned, you know, somewhere in near 60% of our free cash flow back to shareholders. And so, you know, there's lots to, lots of reasons to think about why this, you know, we are a great sort of, I think value creation opportunity and a over the long term that the long term trends are with us, and I expect them to continue to be so, >>Yeah, and you guys, you, you, you do what you say you're gonna do. I mean, I said in my, in my other piece that I did recently, I think you guys put 46 billion on the, on the, on the balance sheet in terms of debt. That's down to I think 16 billion in the core, which that's quite remarking and that gives you some other opportunities. Give us your, your closing thoughts. I mean, you kind of just addressed why Dell is a good long term play, but I'll give you an opportunity to bring us home. >>Hey, Dave. Yeah, look, I, I just think if you look at the good, the market opportunity, the size and scale of Dell and how we think about the competitive advantages that we have, we com you know, if you look at, say we're a hundred billion revenue company, which we were a year, you know, last year, that as we reported roughly 60, 65 billion of that in the client, in in PC space, roughly, you know, 35 to 40 billion in the ISG or infrastructure space, those markets are gonna continue the opportunity to grow, share, grow at a premium to the market, drive, cash flow, drive, share gain is clearly there. You couple that with, you know, what we think the opportunity is in these adjacent markets, whether it's telecom, the edge, what we're thinking around data services, data management, you know, we, and you cut, you put that together with the long term trends around, you know, data creation and digital transformation. We are extraordinarily well positioned. We have the largest direct selling organization in in the technology space. We have the largest supply chain, our services footprint, you know, well positioned in my mind to take advantage of the opportunities as we move forward. >>Well Tom, really appreciate you taking the time to speak with us. Good to see you again. >>Nice seeing you. Thanks Dave. >>All right. You're watching the Cubes exclusive behind the scenes coverage of Dell Technology Summit 2022. In a moment, I'll be back with Jeff Boudreau. He's the president of Dell's ISG Infrastructure Solutions Group. He's responsible for all the important enterprise business at Dell, and we're excited to get his thoughts, keep it right there. >>Welcome back to the cube's exclusive coverage of the Dell Technology Summit. I'm Dave Ante and we're going inside with Dell execs to extract the signal from the noise. And right now we're gonna dig into customer requirements in a data intensive world and how cross cloud complexities get resolved from a product development perspective and how the ecosystem fits in to that mosaic to close the gaps and accelerate innovation. And with me now as friend of the cube, Jeff Boudreau, he's the president of the Infrastructure Solutions Group, ISG at Dell Technologies. Jeff, always good to see you. Welcome. >>You too. Thank you for having me. It's great to see you and thanks for having me back on the cube. I'm thrilled to be here. >>Yeah, it's our pleasure. Okay, so let's talk about what you're observing from customers today. You know, we talk all the time about operating in a data driven multi-cloud world, blah, blah, blah, blah. But what does that all mean to you when you have to translate that noise into products that solve specific customer problems, Jeff? >>Sure. Hey, great question. And everything always starts with our customers. There are motivation, they're top of mind, everything we do, my leadership team and I spend a lot of time with our customers. We're listening, we're learning, we're really understanding their pain points, and we wanna get their feedback in regards to our solutions, both turn and future offerings, really ensure that we're aligned to meeting their business objectives. I would say from these conversations, I'd say customers are telling us several things. First, it's all about data for no surprise going back to your opening. And second, it's about the multi-cloud world. And I'd say the big thing coming from all of this is that both of those are driving a ton of complexity for our customers. And I'll unpack that just a bit, which is first the data. As we all know, data is growing at unprecedented rates with more than 90% of the world's data being produced in the last two years alone. >>And you can just think of that in it's everywhere, right? And so as it as the IT world shifts towards distributed compute to support that data growth and that data gravity to really extract more value from that data in real time environments become inherently more and more hybrid and more and more multi-cloud. Which leads me to the second key point that I've been hearing from our customers, which it's a multi-cloud world, not new news. Customers by default have multiple clouds running across multiple locations that's on-prem and off-prem, it's running at the edge and it's serving a variety of different needs. Unfortunately, for most of our CU customers, multi-cloud is actually added to their complexity. As we've discussed. It's been a lot more of multi-cloud by default versus multi-cloud by design. And if you really think about our customers, I mean, I, I, I've talking to 'EM all the time, you think about the data complexity, that's the growth and the gravity. >>You think about their infrastructure complexity shifting from central to decentralized it, you think about multi-cloud complexity. So you have these walled gardens, if you will. So you have multiple vendors and you have these multiple contracts that all creates operational complexity for their teams around their processes of their tools. And then you think about security complexity that that dries with the, just the increased tax service and the list goes on. So what are we seeing for our customers? They, what they really want from us, and what they're asking us for is simplicity, not complexity. The immediacy, not latency. They're asking for open and aligned versus I'd say siloed and closed. And they're looking for a lot more agility and not rigidity in what we do. So they really wanna simplify everything. They're looking for a simpler IT and a more agile it. And they want more control of their data, right? >>And so, and they want to extract more of the value to enrich their business or their customer engagements, which all sounds pretty obvious and we've probably all heard it a bunch, but it's really hard to achieve. And that's where I believe, and we believe as Dell that we, it creates a big opportunity for us to really help our customers as that great simplifier of it. We're already doing this today on just a couple quick examples. First is Salesforce. We've supported recently, we've supported their global expansion with a multi-cloud solution to help them drive their business growth. Our solution delivered a reliable and consistent IT experience. We go back to that complexity and it was across a very distributed environment, including more than 60 data centers, 230 countries and hundreds of thousands of customers. It really provided Salesforce with the flexibility of placing workloads and data in an environment based on the right service level. >>Objective things like cost complexity or even security compliance considerations. The second customer A is a big New England Patriot fan. And Dan, Dave, I know you are as well. Oh yeah, this one's near, near data to my heart, it's the craft group. We just created a platform to span all the businesses that create more, I'd say data driven, immersive, secure experience, which is allowing them to capture data at the edge and use it for real time insights for things like cyber resiliency, but also like safety of the facilities. And as being a PA fan like I am, did they truly are meeting us where we are in our seats on their mobile devices and also in the parking lot. So just keep that in mind next time you're there. The bottom line, everything we're doing is really to make it simpler for our customers and to help them get the most of their data. I'd say we're gonna do this, is it through a multi-cloud by design approach, which we talked a lot about with you and and others at Dell Tech world earlier this year, >>Right? And we had Salesforce on, actually at Dell Tech group. The craft group is interesting because, you know, when you get to the stadium, you know, everybody's trying to get, get, get out to the internet and, and, but then the experience is so much better if you can actually, you know, deal with that edge. So I wanna talk about complexity though. You got data, you got, you know, the, the edge, you got multiple clouds, you got a different operating model across security model, different. So a lot of times in this industry we solve complexity with more complexity and it's like a bandaid. So I wanna, I wanna talk to, to how you're innovating around simplicity in ISG to address this complexity and what this means for Dell's long term strategy. >>Sure, I'd love to. So first I, I'd like to state the obvious, which are our investments in our innovations really focused on advancing, you know, our, our our customers needs, right? So we are really, our investments are gonna be targeted. We, we believe customers can have the most value. And some of that's gonna be around how we create strategic partnerships as well connected to what we just spoke about. Much of the complexity of customers have or experiencing is in the orchestration and management of all the data in all these different places and customers, you know, they must be able to quickly deploy and operate across cloud environments. They need to increase their developer productivity, really enabling those developers that do what they do best, which is creating more value for their customers than for their businesses. Our innovation efforts are really focused on addressing this by delivering an open and modern IT architecture that allows customers to run and manage any workload in any cloud anywhere. >>Data lives we're focused on, also focused on consumption based solutions, which allow for a greater degree of simplicity and flexibility, which they're really asking for as well. The foundation for this is our software to define common storage layer, that common storage layer. You can think about this Dave, as our ias if you will. It underpins our data access in mobility across all data types and locations. So you can think private, public, telecom, colo, edge, and it's delivered in a secure, holistic, and consistent cloud experience through Apex. We are making a ton of progress to let you just to be, just to be clear, we've made headway in things like Project Alpine, which you're very well aware of. This is our storage as a service. We announce this back in in January, which brings our unique software IP from our flagship storage platform to all the major public clouds. >>Really delivering the best of both worlds, allowing our customers to take advantage of Dell's enterprise class data services and storage software, such as performance at scale, resiliency, efficiency and security. But in addition to that, we're leveraging the breadth of the public cloud services, right? They're on demand scaling capabilities and access to analytical services. So in addition, we're really, we're, we're on our way to win at the edge as well with Project Frontier, which reduces complexity at the edge by creating an open and secure software platform to help our customers simplify their edge operations, optimize their edge environments and investments, secure that edge environment as well. I believe you're gonna be discussing Project Frontier here with Sam Gro Crop, the very near future. So I won't give up too many more details there. And lastly, we're also scaling Apex, which, oh, well, shifting from our vision, really shifting from vision to reality and introducing several new Apex service offerings, which are coming to market over the next month or so. And the intent is really supporting our customers on their as a service transitions by modernize the consumption experience and providing that flexible as a service model. Ultimately, we're trying to help our customers achieve that multi-cloud by design to really simplify it and unlock the power of their data. >>So some good examples there. I I like to talk about the super Cloud as you, you know, you're building on top of the, you know, hyperscale infrastructure and you got Apex is your cloud, the common storage layer, you call it your is. And that's, that's a ingredient in what we call the super cloud out to the edge. You have to have a common platform there and one of the hallmarks of a cloud company. And as you become a cloud company, everybody's a cloud company ecosystem becomes really, really important in terms of product development and, and innovation. Matt Baker always loves to stress it's not a zero zero sum game. And, and I think Super Cloud recognizes that, that there's value to be built on top of other clouds and, and, and of course on top of your infrastructure so that your ecosystem can add value. So what role does the ecosystem play there? >>For me, it's, it's pretty clear. It's, it's, it's critical. I can't say that enough above the having an open ecosystem. Think about everything we just discussed, and I agree with your super cloud analogy. I agree with what Matt Baker had said to you, I would certain no one company can actually address all the pain points and all the issues and challenges our customers are having on their own, not one. I think customers really want and deserve an open technology ecosystem, one that works together. So not these close stacks that discourages interoperability or stifles innovation and productivity of our, of each of our teams. We del I guess have a long history of supporting open ecosystems that really put customers first. And to be clear, we're gonna be at the center of the multi-cloud ecosystem and we're working with partners today to make that a reality. >>I mean, just think of what we're doing with VMware. We continue to build on our first and best alliances with them in August at their VMware explorer, which I know you were at, we announced several joint engineering initiatives to really help customers more easily manage and gain value from their data and their infrastructure. For multi-cloud specifically, we strength our relationship with VMware and with Tansu as part of that. In addition, just a few weeks ago we announced our partnership with Red Hat to simplify our multi-cloud deployments for managing containerized workloads. I'd say, and using your analogy, I could think of that as our multicloud platform. So that's kind of our PAs layer, if you will. And as you're aware, we have a very long standing and strategic partnership with Microsoft and I'd say stay tuned. There's a lot more to come with them and also others in this multicloud space. >>Shifting a bit to some of the growth engines that my team's responsible for the edge, right? As you think about data being everywhere, we've established partnerships for the Edge as well with folks like PTC and Litmus for the manufacturing edge, but also folks like Deep North for the retail edge analytics and data management. Using your Supercloud analogy, Dave the sa, right? This is our Sasa, we've announced that we're collaborating, partnering with folks like Snowflake and, and there's other data management companies as well to really simplify data access and accelerate those data insights. And then given customers choice of where they'd like to have their IT and their infrastructure, we've we're expanding our colo partnerships as well with folks like eex and, and they're allowing us to broaden our availability of Apex, providing customers the flexibility to take advantage of those as a service offerings wherever it's delivered and where they can get the most value. So those are just some you can hear from me. I think it's critical not only for, for us, I think it's critical for our customers. I think it's been critical, critical for the entire, you know, industry as a whole to really have that open technology ecosystem as we work with our customers on our multi-cloud solutions really to meet their needs. We'll continue to collaborate with whoever customers choose and you know, and who they want us to do business with. So I'd say a lot more coming in that space. >>So it's been an interesting three years for you, just, just over three years now since you've been made the president of the IS isg. And so you had to dig in and, and it was obviously a strange time around the world, but, but you really had to look at, okay, how do we modernize the platform? How do we make it, you know, cloud first, You've mentioned the edge, we're expanding. So what are the big takeaways? What do you want customers and our audience to understand? Just some closing thoughts and if you could summarize. >>Sure. So I'd say first, you know, we discussed we're working in a very fast paced, ever-changing market with massive amounts of data that needs to be managed. It's very complex and our customers need help with that complexity. I believe that Dell Technologies is uniquely positioned to help as their multicloud champion. No one else can solve the breadth and depth of the challenges like we can. And we're gonna help our customers move forward when they basically moving from a multi-cloud by default, as we've discussed before, to multicloud by design. And I'm really excited for the opportunity to work with our customers to help them expand that ecosystem as they truly realize the future of it and, and what they're trying to accomplish. >>Jeff, thanks so much. Really appreciate your time. Always a pleasure. Go pats and we'll see you on the blog. >>Thanks Dave. >>All right, you're watching exclusive insight insights from Dell Technology Summit on the cube, your leader in enterprise and emerging tech coverage. >>Hello everyone, this is Dave Lanta and you're watching the Cubes coverage of the Dell Technology Summit 2022 with exclusive behind the scenes interviews featuring Dell executive perspectives. And right now we're gonna explore Apex, which is Dell's as a service offering Dell's multi-cloud and edge strategies and the momentum around those. And we have news around Project Frontier, which is Dell's vision for its edge platform. And there's so much happening here. And don't forget it's cyber security Awareness month. Sam Grot is here, he's the senior vice president of marketing at Dell Technologies. Sam, always great to see you. How you doing? >>Always great to be here, Dave. >>All right, let's look at cloud. Everybody's talking about cloud Apex, multi-cloud, what's the update? How's it going? Where's the innovation and focal points of the strategy? >>Yeah, yeah. Look Dave, if you think back over the course of this year, you've really heard, heard us pivot as a company and discussing more and more about how multi-cloud is becoming a reality for our customers today. And when we listen and talk with our customers, they really describe multi-cloud challenges and a few key threads. One, the complexity is growing very, very quickly. Two, they're having a harder time controlling how their users are accessing the various different clouds. And then of course, finally the cloud costs are growing unchecked as well. So we, we like to describe this phenomenon as multi-cloud by design. We're essentially, organizations are waking up and seeing cloud sprawl around their organization every day. And this is creating more and more of those challenges. So of course at Dell we've got a strong point of view that you don't need to build multicloud by by default, rather it's multicloud by design where you're very intentional in how you do multicloud. >>And how we deliver multicloud by design is through apex. Apex is our modern cloud and our modern consumption experience. So when you think about the innovation as well, Dave, like we've been on a pretty quick track record here in that, you know, the beginning of this year we introduced brand new Apex backup services that provides that SAS based backup service. We've introduced or announced project outline, which is bringing our storage software, intellectual property from on-prem and putting it and running it natively in the public cloud. We've also introduced new Apex cyber recovery services that is simplifying how customers protect against cyber attacks. They can run an Amazon Azure, aw, I'm sorry, Amazon, aws, Azure or Google. And then, you know, we are really focused on this multi-cloud ecosystem. We announce key partnerships with SaaS providers such as Snowflake, where you can now access our information or our data from on-prem through the Snow Snowflake cloud. >>Or if needed, we can actually move the data to the Snowflake cloud if required. So we're continuing to build out that ecosystem SaaS providers. And then finally I would say, you know, we made a big strategic announcement just recently with Red Hat, where we're not only delivering new Apex container services, but we announce the strategic partnership to build jointly engineered solutions to address hybrid and multi-cloud solutions going forward. You know, VMware is gonna always continue to be a key partner of ours at the la at the recent VMware explorer we announced new Tansu integration. So, So Dave, I, I think in a nutshell we've been innovating at a very, very fast pace. We think there is a better way to do multi-cloud and that's multi-cloud by design. >>Yeah, we heard that at Dell Technologies world. First time I had heard that multi-cloud by design versus sort of default, which is great Alpine, which is sort of our, what we called super cloud in the making. And then of course the ecosystem is critical for any cloud company. VMware of course, you know, top partner, but the Snowflake announcement was very interesting Red Hat. So seeing that expand, now let's go out to the edge. How's it going with the edge expansion? There's gotta be new speaking of ecosystem, the edge is like a whole different, you know, OT type, that's right, ecosystem, that's telcos what and what's this new frontier platform all about? >>Yeah, yeah. So we've talked a lot about cloud and multi clouds, we've talked about private and hybrid cloud, we've talked about public clouds, clouds and cos, telcos, et cetera. There's really been one key piece of our multi-cloud and technology strategy that we haven't spent a lot of time on. And that's the edge. And we do see that as that next frontier for our customers to really gain that competitive advantage that is created from their data and get closer to the point of creation where the data lives. And that's at the edge. We see the edge infrastructure space growing very, very quickly. We see upwards of 300% year of year growth in terms of amount of data being created at the edge. That's almost 3000 exabytes of data by 2026. So just incredible growth. And the edge is not really new for Dell. We've been at it for over 20 years of delivering edge solutions. >>81% of the Fortune 100 companies in the US use Dell solutions today at the Edge. And we are the number one OEM provider of Edge solutions with over 44,000 customers across over 40 industries and things like manufacturing, retail, edge healthcare, and more. So Dave, while we've been at it for a long time, we have such a, a deep understanding of how our customers are using Edge solutions. Say the bottom line is the game has gotta change. With that growth that we talked about, the new use cases that are emerging, we've got to un unlock this new frontier for customers to take advantage of the edge. And that's why we are announcing and revealing Project Frontier. And Project Frontier in its most simplest form, is a software platform that's gonna help customers and organizations really radically simplify their edge deployments by automating their edge operations. You know, with Project Frontier organizations are really gonna be able to manage, OP, and operate their edge infrastructure and applications securely, efficiently and at scale. >>Okay, so it is, first of all, I like the name, it is software, it's a software architecture. So presumably a lot of API capabilities. That's right. Integration's. Is there hardware involved? >>Yeah, so of course you'll run it on Dell infrastructure. We'll be able to do both infrastructure orchestration, orchestration through the platform, but as well as application orchestration. And you know, really there's, there's a handful of key drivers that have been really pushing our customers to take on and look at building a better way to do the edge with Project Frontier. And I think I would just highlight a handful of 'em, you know, freedom of choice. We definitely see this as an open ecosystem out there, even more so at the Edge than any other part of the IT stack. You know, being able to provide that freedom of choice for software applications or I O T frameworks, operational technology or OT for any of their edge use cases, that's really, really important. Another key area that we're helping to solve with Project Frontier is, you know, being able to expect zero trust security across all their edge applications from design to deployment, you know, and of course backed by an end and secure supply chain is really, really important to customers. >>And then getting that greater efficiency and reliability of operations with the centralized management through Project Frontier and Zero Touch deployments. You know, one of the biggest challenges, especially when you get out to the far, far reach of the frontier is really IT resources and being able to have the IT expertise and we built in an enormous amount of automation helps streamline the edge deployments where you might be deploying a single edge solution, which is highly unlikely or hundreds or thousands, which is becoming more and more likely. So Dave, we do think Project Frontier is the right edge platform for customers to build their edge applications on now and certain, excuse me, certainly, and into the future. >>Yeah. Sam, no truck rolls. I like it. And you, you mentioned, you mentioned Zero trust. So we have Mother's Day, we have Father's Day. The kids always ask When's kids' day? And we of course we say every day is kids' day and every day should be cybersecurity awareness day. So, but we have cybersecurity awareness month. What does it mean for Dell? What are you hearing from customers and, and how are you responding? >>Yeah, yeah. No, there isn't a more prevalent pop of mind conversation, whether it's the boardroom or the IT departments or every company is really have been forced to reckon with the cybersecurity and ransom secure issues out there. You know, every decision in IT department makes impacts your security profile. Those decisions can certainly, positively, hopefully impact it, but also can negatively impact it as well. So data security is, is really not a new area of focus for Dell. It's been an area that we've been focused on for a long time, but there are really three core elements to cyber security and data security as we go forward. The first is really setting the foundation of trust is really, really important across any IT system. And having the right supply chain and the right partner to partner with to deliver that is kind of the foundation in step one. >>Second, you need to of course go with technology that is trustworthy. It doesn't mean you are putting it together correctly. It means that you're essentially assembling the right piece parts together. That, that coexist together in the right way. You know, to truly change that landscape of the attackers out there that are gonna potentially create risk for your environment. We are definitely pushing and helping to embrace the zero trust principles and architectures that are out there. So finally, while when you think about security, it certainly is not absolute all correct. Security architectures assume that, you know, there are going to be challenges, there are going to be pain points, but you've gotta be able to plan for recovery. And I think that's the holistic approach that we're taking with Dell. >>Well, and I think too, it's obviously security is a complicated situation now with cloud you've got, you know, shared responsibility models, you've got that a multi-cloud, you've got that across clouds, you're asking developers to do more. So I think the, the key takeaway is as a security pro, I'm looking for my technology partner through their r and d and their, you mentioned supply chain processes to take that off my plate so I can go plug holes elsewhere. Okay, Sam, put a bow on Dell Technology Summit for us and give us your closing thoughts. >>Yeah, look, I I think we're at a transformative point in it. You know, customers are moving more and more quickly to multi-cloud environments. They're looking to consume it in different ways, such as as a service, a lot of customers edge is new and an untapped opportunity for them to get closer to their customers and to their data. And of course there's more and more cyber threats out there every day. You know, our customers when we talk with them, they really want simple, consistent infrastructure options that are built on an open ecosystem that allows them to accomplish their goals quickly and successfully. And look, I think at Dell we've got the right strategy, we've got the right portfolio, we are the trusted partner of choice, help them lead, lead their, their future transformations into the future. So Dave, look, I think it's, it's absolutely one of the most exciting times in it and I can't wait to see where it goes from here. >>Sam, always fun catching up with you. Appreciate your time. >>Thanks Dave. >>All right. A Dell tech world in Vegas this past year, one of the most interesting conversations I personally had was around hybrid work and the future of work and the protocols associated with that and the mindset of, you know, the younger generation. And that conversation was with Jen Savira and we're gonna speak to Jen about this and other people and culture topics. Keep it right there. You're watching the cube's exclusive coverage of Dell Technology Summit 2022. Okay, we're back with Jen Vera, who's the chief human resource officer of Dell, and we're gonna discuss people, culture and hybrid work and leadership in the post isolation economy. Jen, the conversations that we had at Dell Tech World this past May around the new work environment were some of the most interesting and engaging that I had personally. So I'm really eager to, to get the update. It's great to see you again. Thanks for coming on the cube. >>Thanks for having me Dave. There's been a lot of change in just a short amount of time, so I'm excited to, to share some of our learnings >>With you. I, I mean, I bet there has, I mean, post pandemic companies, they're trying, everybody's trying to figure out the return to work and, and what it looks like. You know, last May there was really a theme of flexibility, but depending, we talked about, well, millennial or not young old, and it's just really was mixed, but, so how have you approached the topic? What, what are your policies? What's changed since we last talked? You know, what's working, you know, what's still being worked? What would you recommend to other companies to over to you? >>Yeah, well, you know, this isn't a topic that's necessarily new to Dell technology. So we've been doing hybrid before. Hybrid was a thing. So for over a decade we've been doing what we called connected workplace. So we have kind of a, a history and we have some great learnings from that. Although things did change for the entire world. You know, March of 2020, we went from kind of this hybrid to everybody being remote for a while. But what we wanted to do is, we're such a data driven company, there's so many headlines out there, you know, about all these things that people think could happen will happen, but there wasn't a lot of data behind it. So we took a step back and we asked our team members, How do you think we're doing? And we asked very kind of strong language because we've been doing this for a while. >>We asked them, Do you think we're leading in the world of hybrid in 86% of our team members said that we were, which is great, but we always know there's nuance right behind that macro level. So we, we asked 'em a lot of different questions and we just went on this kind of myth busting journey and we decided to test some of those things. We're hearing about Culture Willow Road or new team members will have trouble being connected or millennials will be different. And we really just collected a lot of data, asked our team members what their experience is. And what we have found is really, you don't have to be together in the office all the time to have a strong culture, a sense of connection, to be productive and to have it really healthy business. >>Well, I like that you were data driven around it in the data business here. So, but, but there is a lot of debate around your culture and how it suffers in a hybrid environment, how remote workers won't get, you know, promoted. And so I'm curious, you know, and I've, and I've seen some like-minded companies like Dell say, Hey, we, we want you guys to work the way you wanna work. But then they've, I've seen them adjust and say, Well yeah, but we also want you to know in the office be so we can collaborate a little bit more. So what are you seeing at Dell and, and, and how do you maintain that cultural advantage that you're alluding to in this kind of strange, new ever changing world? >>Yeah, well I think, look, one approach doesn't fit all. So I don't think that the approach that works for Dell Technologies isn't necessarily the approach that works for every company. It works with our strategy and culture. It is really important that we listen to our team members and that we support them through this journey. You know, they tell us time and time again, one of the most special things about our culture is that we provide flexibility and choice. So we're not a mandate culture. We really want to make sure that our team members know that we want them to be their best and do their best. And not every individual role has the same requirements. Not every individual person has the same needs. And so we really wanna meet them where they are so that they can be productive. They feel connected to the team and to the company and engaged and inspired. >>So, you know, for, for us, it really does make sense to go forward with this. And so we haven't, we haven't taken a step back. We've been doing hybrid, we'll continue to do hybrid, but just like if you, you know, we talk about not being a mandate. I think the companies that say nobody will come in or you have to come in three days a week, all of that feels more limiting. And so what we really say is, work out with your team, work out with your role, workout with your leader, what really makes the most sense to drive things forward. >>I >>You were, so >>That's what we, you were talking before about myths and you know, I wanna talk about team member performance cuz there's a lot of people believe that if, if you're not in the office, you have disadvantages, people in the office have the advantage cuz they get FaceTime. Is is that a myth? You know, is there some truth to that? What, what do you think about that? >>Well, for us, you know, we look, again, we just looked at the data. So we said we don't wanna create a have and have not culture that you're talking about. We really wanna have an inclusive culture. We wanna be outcome driven, we're meritocracy. But we went and we looked at the data. So pre pandemic, we looked at things like performance, we looked at rewards and recognition, we looked at attrition rates, we looked at sentiment, Do you feel like your leader is inspiring? And we found no meaningful differences in any of that or in engagement between those who worked fully remote, fully in the office or some combination between. So our data would bust that myth and say, it doesn't, you don't have to be in an office and be seen to get ahead. We have equitable opportunity. Now, having said that, you always have to be watching that data. And that's something that we'll continue to do and make sure that we are creating equal opportunity regardless of where you work. >>And it's personal too, I think, I think some people can be really productive at home. I happen to be one that I'm way more productive in the office cause the dogs aren't barking. I have less distractions. And so I think we think, and, and I think the takeaway that in just in talking to, to, to you Jen and, and folks at Dell is, you know, whatever works for you, we're we're gonna, we're gonna support. So I I wanted to switch gears a little bit, talk about leadership and, and very specifically empathic leadership has been said to be, have a big impact on attracting talent, retaining talent, but, but it's hard to have empathy sometimes. And I know I saw some stats in a recent Dell study. It was like two thirds the people felt like their organization underestimates the people requirements. And I, I ask myself, I'm like, what am I missing? I hope, you know, with our folks, so especially as it relates to, to transformation programs. So how can human resource practitioners support business leaders generally, specifically as it relates to leading with empathy? >>I think empathy's always been important. You have to develop trust. You can have the best strategy in the world, right? But if you don't feel like your leader understands who you are, appreciates the the value that you bring to the company, then you're not gonna get very far. So I think empathetic leadership has always been part of the foundation of a trusting, strong relationship between a leader and a team member. But if I think we look back on the last two years, and I imagine it'll be even more so as we go forward, empathetic leadership will be even more important. There's so much going on in the world, politically, socially, economically, that taking that time to say you want your team members to see you as credible, that you and confident that you can take us forward, but also that, you know, and understand me as a human being. >>And that to me is really what it's about. And I think with regard to transformation that you brought up, I think one of the things we forget about is leaders. We've probably been thinking about a decision or transformation for months or weeks and we're ready to go execute, we're ready to go operationalize that thing. And so sometimes when we get to that point, because we've been talking about it for so long, we send out the email, we have the all hands and we just say we're ready to go. But our team members haven't always been on that journey for those months that we have. And so I think that empathetic moment to say, Okay, not everybody is on a change curve where I am. Let's take a pause, let me put myself in their shoes and really think about how we bring everybody along. >>You know, Jen, in the spirit of myth busting, I mean I'm one of those people who felt like that a business is gonna have a hard time, harder time fostering this culture of collaboration and innovation post isolation economy as they, they could pre covid. But you know, I noticed there's a, there's an announcement today that came across my desk, I think it's from Newsweek. Yes. And, and it's the list of top hundred companies recognized for employee motivation satisfaction. And it was really interesting because you, you always see, oh, we're the top 10 or the top hundred, But this says as a survey of 1.4 million employees from companies ranging from 50 to 10,000 employees. And it recognizes the companies that put respect, caring, and appreciation for their employees at the center of their business model. And they doing so have earned the loyalty and respect of the people who work for them. >>Number one on the list is Dell sap. So congratulations SAP was number two. I mean, there really isn't any other tech company on there, certainly no large tech companies on there. So I always see these lists, they go, Yeah, okay, that's cool, top a hundred, whatever. But top one in, in, in an industry where there's only two in the top is, is pretty impressive. And how does that relate to fostering my earlier skepticism of a culture of collaboration? So first of all, congratulations, you know, how'd you do it? And how are you succeeding in, in this new world? >>Well thanks. It does feel great to be number one, but you know, it doesn't happen by accident. And I think while most companies have a, a culture and a spouse values, we have ours called the culture code. But it's really been very important to us that it's not just a poster on the wall or or words on paper. And so we embed our culture code into all of our HR practices, that whole ecosystem from recognition of rewards to performance evaluation, to interviewing, to development. We build it into everything. So it really reflects who we are and you experience it every day. And then to make sure that we're not, you know, fooling ourselves, we ask all of our employees, do you feel like the behaviors you see and the experience you have every day reflects the culture code? And 94% of our team members say that, in fact it does. So I think that that's really been kind of the secret to our success. If you, if you listen to Michael Dell, he'll always say, you know, the most special thing about Dell is our culture and our people. And that comes through being very thoughtful and deliberate to preserve and protect and continue to focus on our culture. >>Don't you think too that repetition and, well first of all, belief in that cultural philosophy is, is important. And then kind of repeating, like you said, Yeah, it's not just a poster in the wall, but I remember like, you know, when we're kids, your parents tell you, okay, power positive thinking, do one to others as others, you know, you have others do it to you. Don't make the say you're gonna do some dumb things but don't do the same dumb things twice and you sort of fluff it up. But then as you mature you say, Wow, actually those were, >>They might have had a >>Were instilled in me and now I'm bringing them forward and, you know, paying it forward. But, but so i, it, it, my, I guess my, my point is, and it's kind of a point observation, but I'll turn it into a question, is isn't isn't consistency and belief in your values really, really important? >>I couldn't agree with you more, right? I think that's one of those things that we talk about it all the time and as an HR professional, you know, it's not the HR people just talking about our culture, it's our business leaders, it's our ceo, it's our COOs ev, it's our partners. We share our culture code with our partners and our vendors and our suppliers and, and everybody, this is important. We say when you interact with anybody at Dell Technologies, you should expect that this is the experience that you're gonna get. And so it is something that we talk about that we embed in, into everything that we do. And I think it's, it's really important that you don't just think it's a one and done cuz that's not how things really, really work >>Well. And it's a culture of respect, you know, high performance, high expectations, accountability at having followed the company and worked with the company for many, many years. You always respect the dignity of your partners and your people. So really appreciate your time Jen. Again, congratulations on being number one. >>Thank you so much. >>You're very welcome. Okay. You've been watching a special presentation of the cube inside Dell Technology Summit 2022. Remember, these episodes are all available on demand@thecube.net and you can check out s silicon angle.com for all the news and analysis. And don't forget to check out wikibon.com each week for a new episode of breaking analysis. This is Dave Valante, thanks for watching and we'll see you next time.

>>Okay, we're back with Jen Vera, who's the Chief Human Resource Officer of Dell, and we're gonna discuss people, culture and hybrid work and leadership in the post isolation economy. Jen, the conversations that we had at Dell Tech World this past May around the new work environment were some of the most interesting and engaging that I had personally. So I'm really eager to, to get the update. It's great to see you again. Thanks for coming on the cube. >>Thanks for having me, Dave. There's been a lot of change and just a short amount of time, so I'm excited to, to share some of our learnings with >>You. I, I mean, I bet there has, I mean, post pandemic companies, they're trying, everybody's trying to figure out the return to work and, and what it looks like. You know, last May there was really a theme of flexibility, but depending, we talked about, well, millennial or not young old, and it's just really was mixed, but, so how have you approached the topic? What, what are your policies? What's changed since we last talked? You know, what's working, what's still being worked? What would you recommend to other companies to over to you? >>Yeah. Well, you know, this isn't a topic that's necessarily new to Dell technology. So we've been doing hybrid before. Hybrid was a thing, so for over a decade we've been doing what we called connected workplace. So we have kind of a, a history and we have some great learnings from that. Although things did change for the entire world. You know, March of 2020, we went from kind of this hybrid to everybody being remote for a while. But what we wanted to do is, we're such a data driven company. There's so many headlines out there, you know, about all these things that people think could happen will happen, but there wasn't a lot of data behind it. So we took a step back and we asked our team members, How do you think we're doing? And we asked very kind of strong language, because we've been doing this for a while. >>We asked them, Do you think we're leading in the world of hybrid? And 86% of our team members said that we were, which is great, but we always know there's nuance right behind that macro level. So we, we asked them a lot of different questions and we just went on this kind of myth busting journey and we decided to test some of those things. We're hearing about Culture Willow Road or new team members will have trouble being connected or millennials will be different. And we really just collected a lot of data, asked our team members what their experiences. And what we have found is really, you don't have to be together in the office all the time to have a strong culture, a sense of connection, to be productive and to have a really healthy business. >>Well, I like that you were data driven around it with the data business here. So, but, but there is a lot of debate around your culture and how it suffers in a hybrid environment, how remote workers won't get, you know, promoted. And so I'm curious, you know, and I've, and I've seen some like-minded companies like Dell say, Hey, we, we want you guys to work the way you wanna work. But then they've, I've seen them adjust and say, Well, yeah, but we also want you to know in the office, so, so we can collaborate a little bit more. So what are you seeing at Dell and, and, and how do you maintain that cultural advantage that you're alluding to in this kinda strange new ever changing world? >>Yeah. Well, I think, look, one approach doesn't fiddle. So I don't think that the approach that works for Dell Technologies is necessarily the approach that works for every company. It works with our strategy and culture. It is really important that we listen to our team members and that we support them through this journey. You know, they tell us time and time again, one of the most special things about our culture is that we provide flexibility and choice. So we're not a mandate culture. We really want to make sure that our team members know that we want them to be their best and do their best. And not every individual role has the same requirements. Not every individual person has the same needs. And so we really wanna meet them where they are so that they can be productive. They feel connected to the team and to the company and engaged and inspired. >>So, you know, for, for us, it really does make sense to go forward with this. And so we haven't, we haven't taken a step back. We've been doing hybrid, we'll continue to do hybrid, but just like if you, you know, we talk about not being a mandate. I think the companies that say nobody will come in or you have to come in three days a week, all of that feels more limiting. And so what we really say is, work out with your team, work out with your role, workout with your leader, what really makes the most sense to drive things forward. >>I >>Mean, you talking, So that's >>What we do. You were talking before about myths and you know, I wanna talk about team member performance cuz there's a lot of people believe that if, if you're not in the office, you have disadvantages, People in the office have the advantage cuz they get FaceTime. Is is that a myth? You know, is there some truth to that? What, what do you think about that? >>Well, for us, you know, we look, again, we just looked at the data. So we said we don't wanna create a have and have not culture that you're talking about. We really wanna have an inclusive culture, We wanna be outcome driven, we're meritocracy. But we went and we looked at the data. So pre pandemic, we looked at things like performance, we looked at rewards and recognition, we looked at attrition rates, we looked at sentiment, Do you feel like your leader is inspiring? And we found no meaningful differences in any of that or in engagement between those who worked fully remote, fully in the office or some combination between. So our data would bust that myth and say, it doesn't, you don't have to be in an office and be seen to get ahead. We have equitable opportunity. Now, having said that, you always have to be watching that data and that's something that we'll continue to do and make sure that we are creating equal opportunity regardless of where you work. >>And it's personal too, I think, I think some people can be really productive at home. I happen to be one that I'm way more productive in the office cuz the dogs aren't barking. I have less distractions. And so, yeah, I think we think, and I think the takeaway that in just in talking to, to, to you Jen and, and folks at Dell is, you know, whatever works for you, we're we're gonna, we're gonna support. So I, I wanted to switch gears a little bit and talk about leadership and, and very specifically empathic leadership has been said to be, have a big impact on attracting talent, retaining talent, but, but it's hard to have empathy sometimes. And I know I saw some stats in a recent Dell study. It was like two thirds the people felt like their organization underestimates the people requirements. And I, I asked myself, I'm like, Hmm, what am I missing? You know, with our folks. So especially as it relates to, to transformation programs. So how can human resource practitioners support business leaders generally, specifically as it relates to leading with empathy? >>I think empathy's always been important. You have to develop trust. You can have the best strategy in the world, right? But if you don't feel like your leader understands who you are, appreciates the the value that you bring to the company, then you're not gonna get very far. So I think empathetic leadership has always been part of the foundation of a trusting, strong relationship between a leader and a team member. But if I think we look back on the last two years, and I imagine it'll be even more so as we go forward, empathetic leadership will be even more important. There's so much going on in the world, politically, socially, economically, that taking that time to say you want your team members to see you as credible, that you and confident that you can take us forward, but also that, you know, and understand me as a human being. >>And that to me is really what it's about. And I think with regard to transformation that you brought up, I think one of the things we forget about is leaders. We've probably been thinking about a decision or transformation for months or weeks and we're ready to go execute, we're ready to go operationalize that thing. And so sometimes when we get to that point, because we've been talking about it for so long, we send out the email, we have the all hands and we just say we're ready to go. But our team members haven't always been on that journey for those months that we have. And so I think that empathetic moment to say, Okay, not everybody is honest change curve where I am. Let's take a pause, let me put myself in their shoes and really think about how we bring everybody along the journey. >>You know, Jen, in the spirit of myth busting, I mean I'm one of those people who felt like that a business is gonna have a hard time, harder time fostering this culture of collaboration and innovation post isolation economy as they, they could pre covid. But you know, I notice there's, there's an announcement today that came across my desk, I think it's from Newsweek. Yes. And, and it's the list of top hundred companies recognized for employee motivation satisfaction. And it was really interesting because you know, you always see, oh, we're the top 10 or the top hundred, But this says as a survey of 1.4 million employees from companies ranging from 50 to 10,000 employees. And it recognizes the companies that put respect, caring, and appreciation for their employees at the center of their business model. And in doing so, have earned the loyalty and respect of the people who worked for them. >>Number one on the list is Dell sap. So congratulations. SAP was number two. I mean, there really isn't any other tech company on there, certainly no large tech companies on there. So I always see these lists like go, yeah, okay, that's cool, top a hundred, whatever. But top one in, in, in an industry where there's only two in the top is, is pretty impressive. And how does that relate to fostering my earlier skepticism of a culture of collaboration? So first of all, congratulations, you know, how'd you do it? And how are you succeeding in, in this new world? >>Well thanks. It does feel great to be number one, but you know, it doesn't happen by accident. And I think while most companies have a, a culture and a spouse values, we have ours called the culture code. But it's really b been very important to us that it's not just a poster on the wall or or words on paper. And so we embed our culture code into all of our HR practices, that whole ecosystem from recognition rewards to performance evaluation, to interviewee to development. We build it into everything. So it really reflects who we are and you experience it every day. And then to make sure that we're not, you know, fooling ourselves, we ask all of our employees, do you feel like the behaviors you see and the experience you have every day reflects the culture code? And 94% of our team members say that, in fact it does. So I think that that's really been kind of the secret to our success. If you, if you listen to Michael Dell, he'll always say, you know, the most special thing about Dell is our culture and our people. And that comes through being very thoughtful and deliberate to preserve and protect and continue to focus on our culture. >>Don't you think too that repetition and, well first of all, belief in that cultural philosophy is, is important. And then kind of repeating, like you said, Yeah, it's not just a poster on the wall, but I remember like, you know, when we're kids, your parents tell you, okay, power positive thinking, do one to others as others, you know, you have others do it to you. Don't make this, you're gonna do some dumb things but don't do the same dumb things twice and you sort of fluff it up. But then as you mature you say, Wow, actually those were, >>They might have had a, values >>Were instilled in me and now I'm bringing them forward and, you know, paying it forward. But, but, so I guess my, my point is, and it's kind of a point observation, but I'll turn it into a question, is isn't isn't consistency and belief in your values really, really important? >>I couldn't agree with you more, right? I think that's one of those things that we talk about it all the time and as an HR professional, you know, it's not the HR people just talking about our culture, it's our business leaders, it's our ceo, it's our COOs, it's our partners. We share our culture code with our partners and our vendors and our suppliers and, and everybody, this is important. We say when you interact with anybody at Dell Technologies, you should expect that this is the experience that you're gonna get. And so it is something that we talk about that we embed in, into everything that we do. And I think it's, it's really important that you don't just think it's a one and done cuz that's not how things really, really work >>Well. And it's a culture of respect. You know, high performance, high expectations, accountability at having followed the company and worked with the company for many, many years. You'd always respect the dignity of your partners and your people. So really appreciate your time Jen. Again, congratulations on being number one. >>Thank you so much. >>You're very welcome. Okay, you've been watching a special presentation of the Cube inside Dell Technology Summit 2022. Remember, these episodes are all available on demand@thecube.net and you can check out silicon angle.com for all the news and analysis. And don't forget to check out wikibon.com each week for a new episode of breaking analysis. This is Dave Ante, thanks for watching and we'll see you next time.

(bright upbeat music) >> Okay, we're back with Jenn Saavedra, who's the Chief Human Resource Officer of Dell and we're going to discuss people culture and hybrid work and leadership in the post isolation economy. Jenn, the conversations that we had at Dell Tech World this past May around the new work environment were some of the most interesting and engaging that I had personally. So I'm really eager to get the update. It's great to see you again. Thanks for coming on theCUBE. >> Thanks for having me, Dave. There's been a lot of change in just a short amount of time. So I'm excited to share some of our learnings with you. >> I mean, I bet there has, I mean post pandemic companies, they're trying everybody's trying to figure out the return to work and what it looks like. Last May there was really a theme of flexibility but depending, and we talked about, well, millennial or not, young, old, and it's just really was mixed. So how have you approached the topic? What are your policies? What's changed since we last talked? What's working, what's still being worked? What would you recommend to other companies to... Over to you. >> Yeah, well, this isn't a topic that's necessarily new to Dell technology. So we've been doing hybrid before hybrid was a thing. So for over a decade we've been doing what we called connected workplace. So we have kind of a history and we have some great learnings from that. Although things did change for the entire world. In March of 2020, we went from kind of this hybrid to everybody being remote for a while. But what we wanted to do is we're such a data-driven company. There's so many headlines out there, about all these things that people think could happen will happen but there wasn't a lot of data behind it. So we took a step back and we asked our team members, how do you think we're doing? And we asked very kind of strong language because we've been doing this for a while, we asked them, do you think we're leading in the world of hybrid? And 86% of our team members said that we were which is great, but we always know there's nuance behind that macro level. So we asked 'em a lot of different questions and we just went on this kind of myth busting journey and we decided to test some of those things we're hearing about Culture Willow Road or new team members will have trouble being connected or millennials will be different. And we really just collected a lot of data asked our team members what their experiences. And what we have found is really you don't have to be together in the office all the time to have a strong culture, a sense of connection, to be productive, and to have a really healthy business. >> Well, I like that you were data driven around it with the data business here. But there is a lot of debate around your culture and how it suffers in a hybrid environment, how remote workers won't get promoted. And so I'm curious, and I've seen some like-minded companies like Dell say, Hey, we want you guys to work the way you want to work. But then I've seen them adjust and say, Well, yeah, but we also want you to know in the office week so we can collaborate a little bit more. So what are you seeing at Dell and do you maintain that cultural advantage that you're alluding to in this kind of strange new ever changing world? >> Yeah, well, I think, look, one approach doesn't fiddle. So I don't think that the approach that works for Dell Technologies is necessarily the approach that works for every company. It works with our strategy and culture. It is really important that we listen to our team members and that we support them through this journey. They tell us time and time again one of the most special things about our culture is that we provide flexibility and choice. So we're not a mandate culture. We really want to make sure that our team members know that we want them to be their best and do their best. And not every individual role has the same requirements. Not every individual person has the same needs. And so we really want to meet them where they are so that they can be productive. They feel connected to the team and to the company and engaged and inspired. So, for us it really does make sense to go forward with this. And so we haven't taken a step back. We've been doing hybrid, we'll continue to do hybrid. But just like if you, we talk about not being a mandate. I think the companies that say nobody will come in or you have to come in three days a week, all of that feels more limiting. And so what we really say is, work out with your team, work out with your role, work out with your leader what really makes the most sense to drive things forward. >> I mean, you talk- >> So that's what we do. >> You were talking before about myths and I want talk about team member performance 'cause there's, a lot of people believe that if you're not in the office, you have disadvantages, people in the office have the advantage 'cause they get FaceTime. Is is that a myth? Is there some truth to that? What do you think about that? >> Well, for us, we look, again we just looked at the data. So we said we don't want to create a have and have not culture that you're talking about. We really want to have an inclusive culture, we want to be outcome-driven. We're a meritocracy. But we went and we looked at the data. So pre pandemic, we looked at things like performance, we looked at rewards and recognition, we looked at attrition rates, we looked at sentiment. Do you feel like your leader is inspiring? And we found no meaningful differences in any of that or in engagement between those who worked fully remote, fully in the office or some combination between. So our data would bust that myth and say, you don't have to be in an office and be seen to get ahead. We have equitable opportunity. Now, having said that, you always have to be watching that data and that's something that we'll continue to do and make sure that we are creating equal opportunity regardless of where you work. >> And it's personal too, I think I think some people can be really productive at home. I happen to be one that I'm way more productive in the office 'cause the dogs aren't barking. I have less distractions. And so, yeah, and I think the takeaway that in just in talking to you Jenn and folks at Dell is, whatever works for you we're going to support. So I wanted to switch gears a little bit and talk about leadership and very specifically, empathic leadership has been said to have a big impact on attracting talent, retaining talent, but it's hard to have empathy sometimes. And I know I saw some stats in a recent Dell study, it was like two thirds of the people felt like their organization underestimates the people requirements. And I asked myself, I'm like, Hmm, what am I missing with our folks? So especially as it relates to transformation programs. So how can human resource practitioners support business leaders generally, specifically as it relates to leading with empathy? >> I think empathy's always been important. You have to develop trust. You can have the best strategy in the world, right? But if you don't feel like your leader understands who you are, appreciates the value that you bring to the company then you're not going to get very far. So I think empathetic leadership has always been part of the foundation of a trusting strong relationship between a leader and a team member. But if I think we look back on the last two years and I imagine it'll be even more so as we go forward. Empathetic leadership will be even more important. There's so much going on in the world, politically, socially, economically, that taking that time to say you want your team members to see you as credible and confident that you can take us forward, but also that you know and understand me as a human being. And that to me is really what it's about. And I think with regard to transformation that you brought up, I think one of the things we forget about as leaders we've probably been thinking about a decision or transformation for months or weeks and we're ready to go execute, we're ready to go operationalize that thing. And so sometimes when we get to that point because we've been talking about it for so long we send out the email, we have the all hands, and we just say we're ready to go. But our team members haven't always been on that journey for those months that we have. And so I think that empathetic moment to say, Okay, not everybody is on this change curve where I am, let's take a pause, let me put myself in their shoes and really think about how we bring everybody along the journey. >> Jenn, in the spirit of myth busting I mean, I'm one of those people who felt like that a business is going to have a harder time fostering this culture of collaboration and innovation in post isolation economy as they could pre-COVID. But I notice there's an announcement today that came across my desk, I think it's from Newsweek. Yes, and it's the list of top hundred companies recognized for employee motivation, satisfaction. And it was really interesting because you always see, oh, we're the top 10 or the top 100. But this says as a survey of 1.4 million employees from companies ranging from 50 to 10,000 employees. And it recognizes the companies that put respect, caring, and appreciation for their employees at the center of their business model, and in doing so, have earned the loyalty and respect of the people who work for them. Number one on the list is Dell, SAP. So congratulations. SAP was number two. I mean, there really isn't any other tech company on there certainly no large tech companies on there. So I always see these lists, I go, Yeah, okay that's cool, top a hundred, whatever. But top one in an industry where there's only two in the top is pretty impressive. And how does that relate to fostering my earlier skepticism of a culture of collaboration? So first of all, congratulations. How'd you do it? And how are you succeeding in this new world? >> Well, thanks. It does feel great to be number one, but it doesn't happen by accident. And I think while most companies have a culture, and a spouse values, we have ours called the culture code. But it's really been very important to us that it's not just a poster on the wall or words on paper. And so we embed our culture code into all of our HR practices that whole ecosystem, from recognition rewards, to performance evaluation, to interviewee, to development. We build it into everything so it really reflects who we are and you experience it every day. And then to make sure that we're not fooling ourselves, we ask all of our employees, do you feel like the behaviors you see and the experience you have every day reflects the culture code? And 94% of our team members say that in fact it does. So I think that that's really been kind of the secret to our success. If you listen to Michael Dell, he'll always say, "The most special thing about Dell "is our culture and our people." And that comes through being very thoughtful and deliberate to preserve and protect and continue to focus on our culture. >> I don't you think too that repetition and, well, first of all, belief in that cultural philosophy is important. And then kind of repeating, like you said, Yeah it's not just a poster on the wall. But I remember like, when we're kids your parents tell you, okay, power of positive thinking, do unto others as you have others do it to you. You're going to do some dumb things but don't do the same dumb things twice and you sort of fluff it up. But then as you mature you say, Wow, actually those were- >> They might have had a point, right? >> Values were instilled in me and now I'm bringing them forward and paying it forward. But I guess my point is, and it's kind of a point observation but I'll turn it into a question. Isn't consistency and belief in your values really, really important? >> I couldn't agree with you more, right? I think that's one of those things that we talk about it all the time. And as an HR professional, it's not the HR people just talking about our culture. It's our business leaders, it's our CEO, it's our COOs, it's our partners. We share our culture code with our partners and our vendors and our suppliers and everybody, this is important. We say when you interact with anybody at Dell Technologies, you should expect that this is the experience that you're going to get. And so it is something that we talk about that we embed into everything that we do. And I think it's really important that you don't just think it's a one and done 'cause that's not how things really work. >> Well, and it's a culture of respect, high performance, high expectations, accountability, having followed the company and worked with the company for many, many years, you always respect the dignity of your partners and your people. So really appreciate your time, Jenn. Again, congratulations on being number one. >> Thank you so much. >> You're very welcome. Okay, you've been watching a special presentation of theCUBE inside Dell Technology Summit 2022. Remember, these episodes are all available on demand at thecube.net and you can check out siliconangle.com for all the news and analysis. And don't forget to check out wikibon.com each week for a new episode of Breaking Analysis. This is Dave Vellante, thanks for watching and we'll see you next time. (bright upbeat music)

(upbeat music) >> Welcome to this Cube conversation sponsored by Citrix. This is the third and final installment in the Citrix launchpad series. We're going to be talking about the launchpad series for work. Lisa Martin here with Dion Hinchcliffe, VP and principal analyst at Constellation research. Dion, welcome to the program. >> No, thanks Lisa. Great to be here. >> So we have seen a tremendous amount of change in the last 18, 19 months. You know, we saw this massive scatter to work from home a year and a half ago. Now we're in this sort of distributed environment. That's been persisting for a long time. Talk to me about, we're going to be talking about some of the things that Citrix is seeing and some of the things that they're doing to help individuals and teams, but give me your lens from Constellation's perspective. What are some of the major challenges with this distributed environment that you've seen? >> Sure. Well, so we've gone from this, you know, the world of work, the way that it was now, we're all very decentralized, you know, work from anywhere. Remote work is really dominating, you know, white collar types of activities in the workplace and workplaces that in our homes for most of us even today. But that started to change. Some people are going back. Although I just recently spoke to a panel of CIOs that says they have no plans anytime soon, but they're very aware that they need to have workable plans for when we start sending people back to the office and there's this big divide. How are we going to make sure that we have one common culture? We have a collaborative organization when, you know, a good percentage of our workers are in the office, but also maybe as much as half the organization is at home. And so, how to make processes seamless, how to make people collaborate and make sure there's equity and inclusion so that the people at home aren't left out and then people in the office, maybe you don't have an unfair advantage. So those are all the conversations. And of course, because this is a technology revolution, remote work was enabled by technology. We're literally looking at it again for this hybrid work, this, you know, this divided organization that we're going to have. >> You mentioned culture that's incredibly important, but also challenging to do with this distribution. I was looking at some research that Citrix provided, asking individuals from a productivity perspective, and two thirds said, hey, for our organizations that have given us more tools for collaboration and communication, yes, we are absolutely more productive. But the kicker is, the same amount of people, about two thirds that answered the survey said, we've now got about ten tools. So complexity is more challenging. It's harder to work individually. It's harder to work in teams. And so Citrix is really coming to the table here with the launchpad series for work, saying let's help these individuals and these teams, because as we, we think, and I'm sure you have insight Dion on this as well, this hybrid model that we're starting to see emerge is going to be persistent for a while. >> Yeah. For the foreseeable future. Cause we don't know what the future holds. So we'll have to hold the hybrid model as the primary model. And we may eventually go back to the way that we were. But for the next several years, there's going to be that. And so we're trying to wrap our arms around that. And I think that we're seeing with things like the Citrix announcements, a wave of responses saying, all right, let's really design properly for these changes. You know, we kind of just adapted quickly when everyone went to remote last year and now we're actually adding features to streamline, to reduce the friction, to simplify remote work, which does use, you have to use more applications. You have to switch between different things. You have to, you know, your employee experience in the digital world is just more cluttered and complicated, but it doesn't have to be. And so I, you know, we can look to some of these announcements for last year, I think address some of that. >> Let's break some of that down because to your point, it doesn't have to be complex complicated. It shouldn't be. Initially this scatter was, let's do everything we can to ensure that our teams and our people can be productive, can communicate, can collaborate. And now, since this is going to be persistent for quite some time, to your point, let's design for this distributed environment, this hybrid workforce of the future. Talk to me about the, one of the things that Citrix is doing with Citrix workspace, the app personalization, I can imagine as an individual contributor, but also as a team leader, the ability to customize this to the way that I work best is critical. >> And it really is, especially when you know, you have workers, you know, 18 or 19 months worth of new hires that you've never met. They don't really feel like, you know, this is maybe their organization. But if you allow them to shape it a little bit, make it contextual for them. So they don't just come into this cookie cutter digital experience that actually is kind of more meaningful for them. It makes it easier for them to get their job done and things are the way that they want them and where they want them. I think that makes a lot of sense. And so the app personalization announcements is important for remote workers in particular, but all workers to say, hey, can I start tailoring, you know, parts of my employee experience? So they make more sense for me. And I feel like I belong a little bit more. I think it's significant. >> It is. Let's talk about it from a security perspective though. We've seen massive changes in the security landscape in the last year and a half. We've seen some Citrix data that I was looking at, said between 2019 and 2020, ransomware up 435%, malware up 358%. And of course the weakest link being humans. Talk to me from a Citrix workspace perspective about some of the things that they've done to ensure that those security policies can be applied. >> Well, and the part that I really liked about the launchpad announcements around work in terms of security was this much more intelligent analysis. You know, one of the most frustrating things is you're trying to get work done remotely and maybe you're you're in crunch mode and all of a sudden the security system clamps down because they think you're doing something that, you know, you might be sharing information you shouldn't be and now you can't, get your deadline met. I really liked how the analytics inside the new security features really try to make sure they're applying intelligent analysis of behavior. And only when it's clear that a bad actor is in there doing something, then they can restrict access, protect information. And so I have no doubt they'll continue to evolve the product so that it's even even more effective in terms of how it can include or exclude bad actors from doing things inside your system. And so this is the kind of intelligence security increasingly based on AI type technologies that I think that will keep our workers productive, but clamp down on the much higher rate of that activity we see out there. Because we do have so many more endpoints there's a thousand or more times more endpoints in today's organizations because of remote work. >> Right. And one of the things that we've seen with ransomware, I mentioned those numbers that Citrix was sharing. It's gotten so much more personalized, so it's harder and harder to catch these things. One of the things that I found interesting, Dion, that from a secure collaboration perspective, that Citrix is saying is that, you know, we need to go, security needs to go beyond the devices and the endpoints and the apps that an employee is using, which of which we said, there are at least 10 apps that are being used today and it needs to actually be applied at a content level, the content creation level. Talk to me about your thoughts about that. >> I think that's exactly right. So if you know the profile of that worker and the types of things they normally do, and you see unusual behavior that is uncharacteristic to that worker, because you know their patterns, the types of content, the locations of that content that they might normally have access to. And if they're just accessing things, you know, periodically, that's usually not a problem. When they suddenly access a large volume of information and appear to be downloading it, those are the types of issues and especially of content they don't normally use for their work. Then you can intervene and take more intelligent actions as opposed to just trying to limit all content for example. So that knowledge workers can actually get access to all that great information in your IT systems. You can now give them access to it, but when clearly something, something bad is happening, the system automatically does it and steps in. >> I was looking at some of the data with respect to updates to Citrix analytics that it can now auto change permissions on shared files to read only, I think you alluded to this earlier, when it detects that excess sharing is going on. >> And, inappropriate access sharing. So sometimes it's okay for a worker to access, you know, documents. But the big fear is that a bad actor gets access. They get a USB key and they download a bunch of files and they get a whole bunch of IP or important knowledge. Well, when you have a system that's continually monitoring and you know, the unblinking gaze of Citrix security capabilities are looking at the patterns, not just the content alone or just the device alone, but at the, at the usage patterns and saying, I can make this read only because that's clearly the, you know, we don't want them to be able to download this because this activity is completely out of bounds or very unusual. >> Right. One of the things also that Citrix is doing is integrating with Microsoft teams. I was listening to a fun quiz show the other day that said, what were the top two apps downloaded in 2020? And I guessed one of them correctly, Tiktok though. I still don't know how to use it. And the second one was Zoom, and I'm sure Microsoft teams is way up there. I was looking at some stats that said, I think as of the spring of 2020, there were 145 million daily users of Microsoft teams. So that, from a collaboration perspective, something that a lot of folks are dependent on during the pandemic. And now within Teams, I can access Microsoft workspace? Citrix workspace. >> Yes. Well, and it's more significant than it sounds because there's a real hunger to find a center of gravity for the employee experience. What do I put that? Where should they be spending most of their time? Where should I be training them to focus most of their attention? And obviously workers collaborate a lot and Teams as part of Office 365, is a juggernaut? You know, the rise of it during the pandemic has been incredible. And just to show this, I have a digital workplace advisory board. Its companies who are heading, are the farthest along in designing digital employee experiences, and 31% of them said, this January, they're planning on centralizing the employee experience in Teams. Now, if you're a Citrix customer, you have workspace you go, how do I, I don't want to be left out. This announcement allows you to say, you can have the goodness of teams and its capabilities and the power of Citrix workspace, and you have them in one place and really creating a true center of gravity and simplifying and streamlining the employee experience. You don't have this fragmented pieces. Everything's right there in one place, in one pane of glass. And so I like this announcement. It brings Citrix up to parody with a lot of their competitors and actually eclipses several of them as well. So I really like to see this. >> So then from within teams, I can access Citrix workspace. I can share documents with team members and collaborate as well as that kind of the idea. >> Yes. That is the idea, and of course, they'll continue to evolve that, but now you can do your work in Citrix workspace and when documents are involved and you want to bring your team in, they're already right there inside that experience. >> That ability to streamline things, so critical, given the fact that we're still in this distributed environment, I'm sure families are still dealing with some, some amount of remote learning, or there's still distractions from the, do I live at work, do I work from home environment? One of the grips I really felt for when this happened, Dion, was the contact center. I thought these poor people, more people now with shorter and shorter fuses trying to get updates on whatever it was that they were, if they had something ordered and of course all the shipping delays. And the contact center of course went (blowing sound) scattered as well. And we've got people working from home, trying to do their jobs. Talk to me about some of those things that Citrix is doing to enable with Google, those contact center workers to have a good experience so that ultimately the employee experience is good, so is the customer experience? >> The contact center worker has the toughest of all of the different employee profiles I've seen, they have the most they have to learn, the most number of applications. They're typically not highly skilled workers. So they might only just have a, you know, high school education. Yet, they're being asked to cram all of these technologies, each one with a different employee experience, and they don't stay very long as a result of that. You might train them for two months before they're effective and they only stay for six months on average. And so, both businesses really want to be able to streamline onboarding and provisioning a and getting them set up and effective. And they want it too, if you want happy contact center workers making your customers happy and staying around. And so this announcements really allows you to deploy pre-configured Citrix workspaces on, on Chrome OS so that, you know, if you need to field a whole bunch of workers or you have a big dose say you're a relief company and you have a lot of disaster care workers. You can certainly this issue that these devices very easily, they're ready to go with their employee experience and all the right things in place so they can be effective with the least amount of effort. So I guess, it's a big step forward for a worker that is often neglected and underserved. >> Right. Definitely often neglected. And you, you brought up a good point there. And one of the things that, that peaked in my mind, as you talked about, you know, the onboarding experience, the retention, well, these contact center folks are the front lines to the customer. So from a brand reputation perspective, that's on the line, for companies in every industry where people with short fuses are dealing with contact center folks. So the ability to onboard them to give them a much more seamless experience is critical for the brand reputation, customer retention for every industry, I would imagine. >> Absolutely. Especially when you're setting up a contact center or you have a new product launching and you want, you know, you've got to bring, onboard all these new workers, you can do it, and they are going to have the least challenges. They're going to be ready to go right out of the box, be able to receive their package, with their device and their Citrix employee experience, ready to go. You know, just turn the machine on and they're off to the races. And that's the vision and that's the right one. So I was glad to see that as well. >> Yeah. Fantastic. One of the things also that Citrix did, the Citrix workspace app builder, so that Citrix workspace can now be a system of record for certain things like collaboration, surveys, maybe even COVID-19 information, that system of record. Talk to me about why that's so critical for the distributed worker. >> So we've had this, this longstanding challenge in that we've had our systems of record, you know, these are CRM systems, ERP, things like that, which we use to run our business. And then we've had our collaboration tools and they're separate, even though we're collaborating on sales deals and we're collaborating on our supply chain. And so like, the team's announcement was in the same game. We can say, let's close that gap between our systems of record and our collaboration tools. Well, this announcement says, all right, well, we still have these isolated systems of record. How can we streamline them to build and start connecting together a little bit so that we have processes that might cross all of those things, right? It's still going to order comes in from the CRM system. Then you can complete it in the, in the ERP system, you know, ordering that product for them. So they actually get it. You know, and that's probably overkill, that scenario for this particular example. But for example, collecting data from workers saying, let's build some forms and collect some data and then feed it to this process, or this system record. You can do it much more easily than before, before you would have to hire a development team or a contractor to develop another system that would integrate, you know, CRM or ERP or whatever. Now you can do it very quickly inside that builder. First simple, basic applications, and get a lot of the low hanging fruit off your plate and more automated inside of your Citrix workspace. >> And automation has been one of the keys that we've seen to streamlining worker productivity in the last 18 months. Another thing that I was looking at is, you know, the fact that we have so many different apps and we're constantly switching apps, context is constantly changing. Is this sort of system of record going to allow or reduce the amount of context switching that employees have to do? >> Yep. Almost all of these announcements have some flavor to that saying, can we start bringing more systems together in one place? So you're not switching between applications. You don't have different and disconnected sets of data that if you need to, and if they are disconnected, you can connect them, right. That's what the app builder announcement again is about saying, all right, if you're already, always using these three applications to do something, and you're switching between them, maybe you can just build something that connect them into one experience and, you know, maybe a low level of IT person, or even a business user can do that. That's the big trend right now. >> That's so important for that continued productivity, as things will continue to be a little bit unstable, I guess, for awhile. One more thing that I saw that Citrix is announcing is integrations with, Wrike I've been a Wrike user myself. I like to have program project management tools that I can utilize to keep track of projects, but they've done a number of integrations, one of them with Wrike Signature, which I thought was really cool. So for, to secure e-signature within Wrike, based on a program or a project that you're working on. Talk to me about some of the boosts to Wrike that they've done and how you think that's going to be influential in the employee experience. >> Well, first let's just say that the Wrike acquisition was a really important one for Citrix to go above just the basic digital workplace and simple systems of record. This is a really a mass collaboration tool for managing work itself. And so they're, this is taking Citrix up the stack in the more sophisticated work scenarios. And, and when you, we are in more sophisticated work scenarios, you want to be able to pull in different data sets. So, you know, they have the Citrix ShareFile support. You want to be able to bring in really important things like, you know, signing contracts or signing sales deals or mortgage applications, or all sorts of exciting things that actually run in your business. And so, Wrike Signatures, support's really important so that when you have key processes that involve people putting signatures on documents, you can just build collaborative work management flows that, that take all that into account without having to leave the experience. Everything's in one place as much as possible. And this is the big push and we need to have all these different systems. We don't have too many apps. What we have is too many touchpoints, so lets start combining some of these. And so the Wrike integrations, really help you do that. >> Well, and ultimately it seems like what Citrix is doing with the work launchpad series. All the announcements here is really helping workers to work how and where they want to work. Which is very similar to what we say when we're talking about the end user customer experience. When tech companies like Citrix say, we have to meet our customers where they are, it sounds like that's the same thing that's happening here. >> It is. And I would just add on top of that and to make it all safe. So you can bring all these systems together, work from anywhere, and you can feel confident that you're going to do so securely and safely. And it's that whole package I think that's really critical here. >> You're right, I'm glad you brought up that security. All right, Dion take out your crystal ball for me. As we wrap things up, you're saying, you know, going into the future, we're going to be moving from this distributed workforce to this hybrid. What are some of the things that you see as really critical happening in the next six to nine months? >> Well, there's a real push to say, we need to bring in all the workers that we've hired over the last year. Maybe not bringing them in, in person, but can we use these collaborative tools and technologies to bring them, hold them closer so they get to know us. And so, you know, things like, having Microsoft teams integrated right into your Citrix workspace makes it easier for you to collaborate with remote workers and inside any process wherever you are. So whether you're in the office or not, it should bring workers closer, especially those remote ones that are at risk of being left out as they move to hybrid work. And then it's really important. And so the things like the app builder are going to also allow building those connections. And I think that workers and businesses are really going to try and build those bridges, because the number one thing I'm hearing from business leaders and IT leaders is, is it, you know, we're worried about splitting into two different organizations, the ones that are remote and the ones that are in the office and any way that we can bring all of them together in an easy way, in a natural way, situate the digital employee experience so that we really back or back to one company, one common culture, everybody has equal access and equity to the employee experience. That's going to be really important. And I think that Citrix launchpad announcements around work really are a step, a major step in the right direction for that. There's still more things that have to be done and all, all vendors are working on that. But it's nice to see. I really liked what Citrix is doing here to move the ball forward towards where we're all going. >> It is nice to see, and those connections are critically important. I happen to be at an in-person event last week, and several folks had just had been hired during the pandemic and just got to meet some of their teams. So in terms of, of getting that cultural alignment, once again, this is a great step towards that. Dion thank you for joining me on the program, talking about the Citrix launchpad series for work, all the great new things that they're announcing and sharing with us as some of the things that you see coming down the pike. We appreciate your time. >> Thanks Lisa, for having me. >> For Dion Hinchcliffe. I'm Lisa Martin. You're watching this Cube conversation. (upbeat music)

>> Announcer: From the Bellagio Hotel in Las Vegas, it's theCUBE, covering UiPath FORWARD IV brought to you by UiPath. >> Live from Las Vegas, it's theCUBE. We are wrapping up day two of our coverage of UiPath FORWARD IV. Lisa Martin here with Dave Vellante. We've had an amazing event talking with customers, partners, and users, and UiPath folks themselves. And who better to wrap up the show with than Daniel Dines the founder and CEO of UiPath. Welcome, Daniel, great to have you back on theCUBE. >> Oh, thank you so much for having me. I'm becoming a regular at theCUBE. >> Yeah, it's good to see you again. >> You are, this is your fifth... >> Fifth time on theCUBE. >> Fifth time, yes. >> Fifth time, but as you said before we went live, first time since the IPO. Congratulations. >> Thank you. >> UiPath has been a rocket ship for a very long time. I'm sure a tremendous amount of acceleration has occurred since the IPO. We can all see the numbers. You're a public company now, ARR of 726 million. You've got over 9,000 customers. We got the chance to speak with a few of them here today. We know how important the voice of the customer is to UiPath and how very symbiotic it is. But I want to talk about the culture of the company. How is that going? How is it being maintained especially since the big splashy IPO just about six months ago? >> Well, I always believe that in order to build a durable company, culture is maybe the most important thing. I think long lasting companies have very foundational culture. So we've built it, and we invested a lot in the last 5-6 years because in the beginning when it's just a bunch of people, they don't have a culture. It's maybe like a vibe of a group of friends. But then when you go and try to dial in your culture, I think it's important that you look at your roots and who are you? What defines you? So we ended up of this really core values, which is to be humble. To me, it's one of quintessential value of every human being. And all of us want to work with humble people much more inclined to listen, to change their mind. And then we say, you have to be humble, but you have to be bold in the same time. This rocket ship need a bold crew onboard. So you need to be fast because the fastest company will always win. And you need to be immersed because my theory with life and jobs is in whatever you do, you have to be immersed. I don't believe necessarily in life-work balance. I believe in life-work cycles, in life-work immersion. So when you are with family, you are immersed. When you work, you are immersed. That will bring the best of you and the best of productivity. So we try so much to keep our culture alive, to hire people that add to the culture, that nicely fit into the culture. And recently we took a veteran of UiPath and we appointed her as Chief Culture Officer. So I'm very happy of this move. So I think we are one of the few companies that really have a Chief Culture Officer reporting directly to the CEO. So we're really serious of building our culture along the way. And as I said yesterday in my keynote, I think our values are universal values. I think they have the value of the new way of working. All of us would like to work in a company, in an environment that fosters these values. >> I certainly think the events of the last 18 months have forced many more people to be humble and embrace humility. Because everybody on video conferencing, your dog walks in, your kids walk in, you're exposed. They have to be more humble because that's just how they were getting work done. I've seen and heard a lot of humility from your folks and a lot of bold statements from customers as well. We had the CIO of Coca-Cola on talking about how UiPath is fundamental in their transformation. I think that the fact that you are doing an event here in person, whereas as Dave was saying earlier this week, your competitors are on webcams is a great example of the boldness of this company and its culture. >> Well, thank you. I think that we've made a really good decision to do this event in person. Maybe on Zoom over the last 18 months, we kind of lost a bit how important is to connect with people. It's not only about the message, it's about the trust. And I think we are deeply embedded into the critical systems of our customers. They need to trust us. They need to work with the company that they look in their eyes and say, "Yes, we are here for you." And you cannot do it over Zoom. Even I really like Zoom and Eric Yuan is a friend of mine, but a combination I think, and going into this hybrid world, I think it's actually extremely beneficial for all of us. Meeting in person a few times a year, then continuing the relationship over Zoom in time, I think it's awesome. >> Yeah, and the fact that you were able to get so many customers here, I think that's, Lisa, why a lot of companies don't have physical events 'cause they can't get their customers here. You got 2000 customers here, customers and partners, but a lot of customers. I've spoken to dozens and they're easy to find. So I think that's one point I want the audience to know. You've always been on the culture train. And enduring companies, CEOs of great enduring companies, always come back to culture. So that's important. And of course, product. You said today, you're a product guy. That's when you get excited. You've changed the industry. And I think, I've never bought into the narrative about replacing jobs. I'd never been a fan of protecting the past from the future. It's inevitable, but I think the way you've changed the market, I wonder if you could comment is... You had legacy RPA tools that were expensive and cumbersome. And so people had to get the ROI and it took a long time. So that was an obvious way to get it is to reduce headcount. You came in and said, short money you can actually try it even a free version. You compressed that ROI and the light bulb went off, and so people then said, "Oh, wow, this isn't about replacing jobs, but making my life better." And you've always said that. And that's I think one way in which you've changed the market quite dramatically, and now you have a lot of people following that path. >> That was always kind of our biggest competitive advantage. We showed our customers and our partners, this is a technology that gives you the faster time to value and actually faster time to value translate into much higher return on investment. In a typical automation project, the license cost is maybe 5% of the project cost. So the moment you shrink the development time, the implementation time, you increase exponentially the return on investment. So this is why speaking about our roadmap, and we always start with this high level, how can we reduce the development time? So how can we reduce the friction? How can we expand the use cases? Because these are essential themes for us, always thinking customer first, customer value and that serves us pretty well really. We win a lot in all the contests where we go side by side with other competitors. It was a very simple strategy for us. Asking customers, "Just go and test it side-by-side and see," and they see. We implement the same process in halftime, half of resources involved. It's an easy math multiplied by a thousand processes and it's done. >> When theCUBE started Daniel in 2010. It was our first year. And so it coincided with big data movement. And we said at the time that the companies who can figure out how to apply big data are going to make a lot of money, more than the big data vendors. And I think in a way now the problem with big data was too complicated, right? There were only a few big internet giants who could figure out Hadoop and all that stuff. Automation, I think is even bigger in a way, 'cause it involves data. It involves AI, it's transformative. And so we're saying the same thing here. The companies that are applying automation, and we've seen a lot of them here, Coca-Cola, Merck, Applied Materials, on and on and on, are actually the ones that are going to not only survive but thrive, incumbents that don't have to invent AI necessarily or invent their own automation. But coming back to you 'cause I think your company can make a lot of money. You've set the TAM at 60 billion. I think it actually could be well over 100 billion, but we don't have to have that conversation here. It's just convergence of all these markets that guys like IDC and Gartner, they count in stove pipes. So anyway, big, no shortage of opportunity. My question to you is feels like you have the potential to build a next great software company and with the founder as the CEO, and there aren't a lot of them left. Michael Dell is not a software company, but his name is still, Larry Ellison is still there, Marc Benioff. How do you think about the endurance, the enduring UiPath? Are you envisioning building the next great software company, may take 20 years? >> People were asking me for a long time. Did you envision that you'd get here from the beginning? And I always tell them, no. Otherwise I would have been considered mad. (Lisa and Dave laughing) So you build the vision over time. I don't believe in people that start a small SaaS company and they say, "We are going to change the world." This is not how the world works. Really, you build and you understand the customer and you build more. But at some point I realized we change so much how people work, we get the best out of them. It's something major here. And if you look in history, we are in this trap that started with agriculture. This is the trap of manual, repetitive, low value tasks that we have to do. And it took the humanity of us. And I talked to Tom Montag about with this book "Sapiens". It's interesting and that book comes with the theory that our biggest quality is our ability to collaborate. Well, our technology gives people the ability to collaborate more. So, in this way, I think it's truly transformative. And yes, I believe now that we can build the next generation of software company. >> How do you like... That's the wrong question. How are you doing with the 90-day shot clock as Michael Dell calls it? It's a new world for you, right? You've never been a CEO of a public company, the street's getting to know you like, "Who is this guy?" I'll give you another cute story. There were three companies in the early CUBE days, Tableau, Splunk, and ServiceNow that had the kind of customer passion that you have. I think ServiceNow could be one of the next great software companies. Tableau now part of Salesforce. I think Splunk was under capitalized, but we see the same kind of passion here. So now you're the CEO of a public company, except the street's getting to know you a little bit. They're like, "Hmm, how do we read the guy?" All that stuff. That'll sort itself out. But so what's life like on the public markets? >> Well, I don't think anyone prepares you for the life of a public company. (Dave laughing) I thought it's going to be easier, but it's not, because we were used to deal with private investors and it's much easier because I think private investors have access to a lot more data. They look into your books. So they understand your business model. With public investors, they have access only to like a spreadsheet of numbers. So they need to figure out a business model, the trajectory from just a split. It's way more difficult. I've come to appreciate their job. It's much more difficult. So they have to get all the cues from how I dress, how do I say this word? They watch the FED announcements. What do they mean to say by this? And I and the shim we are first time in a job as a public company CEO, public company CFO. So of course it's a lot of learning for us and like in any learning environment, initial learning curve is tough, but you progress quite a lot. So I believe that over the next few quarters, we will be in the position to build trust with the street and they will understand better our business model, and they see that we are building everything for creating durable growth. >> It's a marathon, it's not a sprint. I know it's a cliche, but it really does apply here. >> You've certainly built a tremendous amount of trust within your 9,000 strong customer base. I think I was reading that your 70% of your revenue comes from existing customers. I think this is a great use case for how to do land and expand really well. So, the DNA I think is there at UiPath to be able to build that trust with the street. >> Yeah, absolutely. Our 9,000 plus customers, it's our wealth. This is our IP in a way. It's even better than in our pro. It's our customers. We have one of the best net retention rate in the industry of 144%. So that speaks volume. >> Lisa: It does. >> Automation for good. I know you've read some of the stuff I've written. I've covered you guys pretty extensively over the years. And that theme sounds like a lot of motherhood and apple pie, but one of the things that I wrote is that you look at the productivity decline and particularly in Western countries over the last two decades. Now I know with the pandemic and especially in 2021, productivity is going up for reasons that I think are understood, but the trend is clear. So when you think about big problems, climate change, diversity, income inequality, health of populations, overpopulation, on and on and on and on. You're not going to solve those problems by throwing labor at them. It has to be automation. So that to me is the tie to automation for good. And a lot of people might roll their eyes at it. But does that resonate with you? >> It totally resonates with me. Look at US. US population is not growing at the rates that we were used to. It's going to plateau at some point. It's just obvious. Like it plateaued in Japan, in Japan it's decreasing. US will see a decrease at some point. How do you increase the GDP? If your population is declining, productivity is declining. How do you increase GDP? Because the moment we stop increasing GDP, everything will collapse. The modern world is built on the idea of continuous economical growth. The moment growth stops, the world stops. We'll go back to our case and restart the engine. So, automation is hugely important in continuous GDP growth, which is the engine of our life. >> Which by the way is important because the chasm between the haves and the have-nots, that's how growth allows the people at the bottom to rise up to the middle and the middle to the top. So that's how you deal with that problem. You asked Tom Montag about crypto. So I have to ask you about crypto. What are your thoughts? Are you a fan? Are you not a fan? Do you have any wisdom? >> I have to admit, I never really understood the use cases of crypto. Technology behind crypto, blockchain is fascinating technology, but crypto in itself, I was never a fan. Tom Montag today gave me one of the best explanation of the very same. Look, Daniel, from Americans perspective we have the dollars, and this is the global currency. Crypto doesn't have so much sense, but think about a country like Columbia or Venezuela, countries where there people don't have so much trust in their currency, and where different political system can seize your assets from you. You need to be able to be capable of putting them into something else that is outside government context. I believe this is a good use case but I still don't believe that crypto is that type of asset that you know will survive the test of time. I think it's really too much... To me the difference between gold and Bitcoin is that it's too... You cannot replicate gold whatever you... It's impossible, unless you are God you cannot create gold two, right? It's impossible, but you can create Bitcoin 2. And at some point the fashion will move from Bitcoin 2 to Bitcoin 3. So I don't think the value that you can build in one particular crypto currency right now will stay over time. But it's just me. I was the wrong so many times in my life. >> You've been busy. You haven't had time to study crypto. >> I agree, totally agree. (Lisa and Dave laughing) >> What's been some of the feedback from the customers that are here. We saw yesterday a standing room only keynote. I'm sure it was great for you to be on stage again actually interacting with your customers and your partners. What's been some of the feedback as we've seen really this shift from an RPA point solution to an enterprise automation platform? >> Well, first of all, it was really great to be on stage. I don't know, I'm not a good presenter, really. But going there in front of people felt me with energy. Suddenly I felt a lot of comfort. So, I was capable of being myself with the people, which is really awesome. And the transition to a platform, from a product to a platform was really very well received by our customers because even in our competitive situations, when we are capable of explaining to them, what is the value of having an independent automation platform that is not tied to any big silos that application providers creates, we win and we win by default somehow. You've seen them now. So I think even the next evolution of semantic automation, this one is very well with our customers. >> Well, Daniel, it's been fantastic having you on. We have a good cadence here, and I hope we can continue it. On theCUBE, we love to identify early stage companies. Although as I wrote, you had a long, strange path to IPO because you took a long, long time and I think did it the right way to get product market fit. >> Absolutely. >> And that's not necessarily the way Silicon Valley works, double, double, triple, triple, and that you got product market fit, you got loyal customer base, and I think that's a key part of your success and you can see it and so congratulations, but many more years to come and we're really watching. >> Thank you so much. I'm looking forward to meeting you guys again. Thank you, that was awesome really. Great discussion. >> Exactly, good. Great to have you here in person and thanks for having us here in person as well. We look forward to FORWARD V. >> You will be invited forever. Thank you, guys, really. >> Forever, did you hear that? All right, for Daniel Dines and Dave Vellante, I'm Lisa Martin. This is theCUBE's coverage of UiPath FORWARD IV day two. Thanks for watching. (upbeat music)

>>From around the globe. It's the cube covering data citizens. 21 brought to you by Colibra >>Welcome to the cubes coverage of Collibra data citizens 21. I'm Lisa Martin. I have three guests with me here today. Colibra customer Freddie Mac, please welcome JAG chief data officer and vice president of single family data and decisions. Jog. Welcome to the cube. >>Thank you, Lisa. Look forward to be, >>Uh, excellent on Kiko LSU as well. Vice president data transformation and analytics solution on Kay. Good to have you on the program. >>Thank you, Lisa. Great to be here and >>A teeth Malik senior director from the single family division at Freddie Mac is here as well. A team welcome. So we have big congratulations in order. Uh, pretty Mac was just announced at data citizens as the winners of the Colibra excellence award for data program of the year. Congratulations on that. We're going to unpack that. Talk about what that means, but I'd love to get familiar with the 3d Jack. Start with you. Talk to me a little bit about your background, your current role as chief data officer. >>Appreciate it, Lisa, thank you for the opportunity to share our story. Uh, my name is Arvind calls me Jack. And as you said, I'm just single-family chief data officer at Freddie Mac, but those that don't know, Freddie Mac is a Garland sponsored entity that supports the U S housing finance system and single family deals with the residential side of the marketplace, as CDO are responsible for our managed content data lineage, data governance, business architecture, which Cleaver plays a integral role, uh, in, in depth, that function as well as, uh, support our shared assets across the enterprise and our data monetization efforts, data, product execution, decision modeling, as well as our business intelligence capabilities, including AI and ML for various use cases as a background, starting my career in New York and then moved to Boston and last 20 years of living in the Northern Virginia DC area and fortunate to have been responsible for business operations, as well as led and, um, executed large transformation efforts. That background has reinforced the power of data and how, how it's so critical to meeting our business objectives. Look forward to our dialogue today, Lisa, once again. >>Excellent. You have a great background and clearly not a dull moment in your job with Freddy, Matt. And tell me a little bit about your background, your role, what you're doing at Freddie >>Mac. Definitely. Um, hi everyone. I'm,, I'm vice president of data transformation and analytics solutions. And I worked for JAG. I'm responsible for many of the things he said, including leading our transformation to the cloud and migrating all our existing data assets front of that transformation journey. I'm also responsible for our business information and business data architecture, decision modeling, business intelligence, and some of the analytics and artificial intelligence. I started my career back in the day as a computer engineer, but I've always been in the financial industry up in New York. And now in the Northern Virginia area, I called myself that bridge between business and technology. And I would say, I think over the last six years with data found that perfect spot where business and technology actually come together to solve real problems and, and really lead, um, you know, businesses to the next stage of, so thank you Lisa for the opportunity today. Excellent. >>And we're going to unpack you call yourself the bridge between business and it that's always such an important bridge. We're going to talk about that in just a minute, but I want to get your background, tell our audience about you. >>Uh, I'm Alec Malek, I'm senior director of business, data architecture, data transformation, and Freddie Mac. Uh, I'm responsible for the overall business data architecture and transformation of the existing data onto the cloud data lake. Uh, my team is responsible for the Kleberg platform and the business analysts that are using and maintaining the data in Libra and also driving the data architecture in close collaboration with our engineering teams. My background is I'm a engineer at heart. I still do a lot of development. This is my first time as of crossing over onto the bridge onto business side of maintaining data and working with data teams. >>Jan, let's talk about digital transformation. Freddie Mac is a 50 year old and growing company. I always love talking with established businesses about digital transformation. It's pretty challenging. Talk to me about your initial plan and what some of the main challenges were that you were looking to solve. >>Uh, great question, Lisa, and, uh, it's definitely pertinent as you say, in our digital world or figuring out how we need to accomplish it. If I look at our data, modernization is it is a major program and, uh, effort, uh, in, in our, in our division, what started as a reducing cost or looking at an infrastructure play, moving from physical data assets to the cloud, as well as enhancing our resiliency as quickly morphed into meeting business demand and objectives, whether it be for sourcing, servicing or securitization of our loan products. So where are we as we think about creating this digital data marketplace, we are, we are basically forming, empowering a new data ecosystem, which Columbia is definitely playing a major role. It's more than just a cloud native data lake, but it's bringing in some of our current assets and capabilities into this new data landscape. >>So as we think about creating an information hub, part of the challenges, as you say, 50 years of having millions of loans and millions of data across multiple assets, it's frigging out that you still have to care and feed legacy while you're building the new highway and figuring out how you best have to transform and translate and move data and assets to this new platform. What we've been striving for is looking at what is the business demand or what is the business use case, and what's the value to help prioritize that transformation. Exciting part is, as you think about new uses of acquiring and distribution of data, as well as news new use cases for prescriptive and predictive analytics, the power of what we're building in our daily, this new data ecosystem, we're feeling comfortable, we'll meet the business demand, but as any CTO will tell you demand is always, uh, outpaces our capacity. And that's why we want to be very diligent in terms of our execution plan. So we're very excited as to what we've accomplished so far this year and looking forward as we offered a remainder year. And as you go into 2022. Excellent, >>Thanks JAG. Uh, two books go to you. As I mentioned in the intro of that Freddie Mac has won the Culebra excellence award for data program of the year. Again, congratulations on that, but I'd love to understand the Kleber center of excellence that you're building at Freddie Mac. First of all, define what a center of excellence is to Freddie Mac and then what you're specifically building. Yeah, sure. >>So the Cleaver center of excellence provides us the overall framework from a people and process standpoint to focus in on our use of Colibra and for adopting best practices. Uh, we can have teams that are focused just on developing best practices and implementing workflows and lineage within Collibra and implementing and adopting a number of different aspects of Libra. It provides the central hub of people being domain experts on the tool that can then be leveraged by different groups within the organization to maintain, uh, the tool. >>Put another follow on question a T for you. How does Freddie Mac define, uh, dated citizens as anybody in finance or sales or marketing or operations? What does that definition of data citizen? >>It's really everyone it's within the organization. They all consume data in different ways and we provide a way of governing data and for them to get a better understanding of data from Collibra itself. So it's really everyone within the organization that way. >>Excellent. Okay. Let's go over to you a big topic at data citizens. 21 is collaboration. That's probably a word that we used a ton in the last 15 plus months or so it was every business really pivoted quickly to figure out how do we best collaborate. But something that you talked about in your intro is being the bridge between business and it, I want to understand from your perspective, how can data teams help to drive improved collaboration between business and it, >>The collaboration between business and technology have been a key focus area for us over the last few years, we actually started an agile transformation journey two years ago that we called modern delivery. And that was about moving away from project teams to persistent product teams that brought business and technology together. And we've really been able to pioneer that in the data space within Freddie Mac, where we have now teams with product owners coming from the data team and then full stack ID developers with them creating these combined teams to meet the business needs. We found that bringing these teams together really remove the barriers that were there in the interaction and the employee satisfaction has been high. And like you said, over the last 16 months with the pandemic, we've actually seen the productivity stay same or even go up because the teams were all working together, they work as a unit and they all have the sense of ownership versus working on a project that has a finite end date to fail. So we've, um, you know, we've been really lucky with having started this two years ago. Well, and >>That's great. And congratulations about either maintaining productivity or having it go up during the last 16 months, which had been incredibly challenging. Jack. I want to ask you what does winning this award from Collibra what does this mean to you and your team and does this signify that you're really establishing a data first culture? >>Great question, Lisa again. Um, I think winning the award, uh, just from a team standpoint, it's a great honor. Uh, Kleber has been a fantastic partner. And when I think about the journey of going from spread sheets, right, that all of us had in the past to now having all our business class returns lineage, and really being at the forefront of our data monetization. So as we think about moving to the cloud Beliebers step in step with us in terms of our integral part of that holistic delivery model, when I ultimately, as a CDO, it's really the team's honor and effort, cause this has been a multi-year journey to get here. And it's great that Libra as a, as a partner has helped us achieve some of these goals, but also recognized, um, where we are in terms of, uh, as looking at data as a product and some of our, um, leading forefront and using that holistic delivery, uh, to, uh, to meet our business objectives. So overall poorly jazzed when, uh, we've been found that we wanted the data program here at Collibra and very honored, um, uh, to, to win this award. That's >>Where we got to bring back I'm jazzed. I liked that jug sticking with you, let's unpack a little bit, some of those positive results, those business outcomes that you've seen so far from the data program. What are those? >>Yeah. So again, if you were thinking about a traditional CDO model, what were the terms that would have been used few years ago? It was around governance and may have been viewed as an oversight. Um, maybe less talking, um, monetization of what it was, the business values that you needed to accomplish collectively. It's really those three building blocks managing content. You got to trust the source, but ultimately it's empowering the business. So the best success that I could say at Freddy, as you're moving to this digital world, it's really empowering the business to figure out the new capabilities and demand and objectives that we're meeting. We're not going to be able to transform the mortgage industry. We're not going to be able or any, any industry, if we're still stuck in old world thinking, and ultimately data is going to be the blood that has to enable those capabilities. >>So if you tell me the business best success, we're no longer talking a okay, I got my data governance, what do we have to do? It's all embedded together. And as I alluded to that partnership between business and it informing that data is a product where you now you're delivering capabilities holistically from program teams all across data. It's no longer an afterthought. As I said, a few minutes ago, you're able to then meet the demand what's current. And how do we want to think about going forward? So it's no longer buzzwords of digital data marketplace. What is the value of that? And that's what the success, I think if our group collectively working across the organization, it's just not one team it's across the organization. Um, and we have our partners, our operations, everyone from business owners, all swimming in the same direction with, and I would say critical management support. So top of the house, our, our head of business, my, my boss was the COO full supportive in terms of how we're trying to execute and I've makes us, um, it's critical because when there is a potential, trade-offs, we're all looking at it collectively as an organization, >>Right. And that's the best viewpoint to have is that sort of centralized unified vision. And as you say, JAG, the support from, from up top, uh, I'd see if I want to ask you, you establish the Culebra center of excellence. What are you focused on now? >>So we really focused in allowing our users to consume data and understand data and really democratizing data so that they can really get a better understanding of that. So that's a lot of our focus and engaging with Collibra and getting them to start to define things in Colibra law form. That's a lot of focus right now. >>Excellent. Want to stay with you one more question and take that I'm gonna ask to all of you, what are you most excited about a lot of success that you've talked about transforming a legacy institution? What are you most excited about and what are the next steps for the data program? Uh, teak what's are your thoughts? >>Yeah, so really modernizing onto, uh, onto a cloud data lake and allowing all of the users and, uh, Freddie Mac to consume data with the level of governance that we need around. It is a exciting proposition for me. >>What would you say is most exciting to you? >>I'm really looking forward to the opportunities that artificial intelligence has to offer, not just in the augmented analytics space, but in the overall data management life cycle. There's still a lot of things that are manual in the data management space. And, uh, I personally believe, uh, artificial intelligence has a huge role to play there. And Jackson >>Question to you, it seems like you have a really strong collaborative team. You have a very collaborative relationship with management and with Collibra, what are you excited about? What's coming down the pipe. >>So Lisa, if I look at it, you know, we sit back here June, 2021, where were we a year ago? And you think about a lot of the capabilities and some of the advancements that we may just in a year sitting virtually using that word jazzed or induced or feeling really great about. We made a lot of accomplishments. I'm excited what we're going to be doing for the next year. So there's other use cases, and I could talk about AIML and OCHA talks about, you know, our new ecosystem. Seeing those use cases come to fruition so that we're, we are contributing to value from a business standpoint. The organization is what really keeps me up. Uh, keeps me up at night. It gets me up in the morning and I'm really feeling dues for the entire division. Excellent. >>Well, thank you. I want to thank all three of you for joining me today. Talking about the successes that Freddie Mac has had transforming in partnership with Colibra again, congratulations on the Culebra excellence award for the data program. It's been a pleasure talking to all three of you. I'm Lisa Martin. You're watching the cubes coverage of Collibra data citizens 21.

(soft music) >> Hey, welcome to this "CUBE Conversation". I'm Lisa Martin today talking to a CUBE alumni who's been on many times talking about data, all things data. Please welcome Satyen Sangani the Co-Founder and CEO of Alation. Satyen, it's great to have you back on theCUBE. >> Hi Lisa, it's great to see you too. It's been a while. >> It has been a while. And of course in the last year we've been living in this virtual world. So, I know you've gotten to be on theCUBE during this virtual world. Hopefully someday soon, we'll get to actually sit down together again. There's some exciting news that's coming out of Alation. Talk to us about what's going on. What are you announcing? >> So we're announcing that we are releasing our Alation Cloud Service which actually comes out today, and is available to all of our customers. And as a consequence are going to be the fastest, easiest deploy and easiest to use data catalog on the Marketplace, and using this release to really double down on that core differentiation. >> So the value prop for Alation has always been about speed to deployment, time to value. Those have really been, what you've talked about as the fundamental strengths of the platform. How does the cloud service double down on that value prop? >> Well, if you think about data, our basic premise and the reason that we exist is that, people could use data with so many of their different decisions. People could use data to inform their thinking. People can use data in order to figure out what decision is the best decision at any given point in time. But often they don't. Often gut instinct, or whatever's most fast or easy to access is the basis off of which people decide to do what they do. And so if you want to get people to use data more often you've got to make sure that the data is available that the data is correct, and that the data is easy to find and leverage. And so everything that we can do at Alation to make data more accessible, to allow people to be more curious, is what we get excited about. Because unlike, paying your payables or unlike, figuring out whether or not you want to be able to have greater or lesser inventory, those are all things that a business absolutely has to do but people don't have to use data. And to get people to use data, the best thing you can do is to make it easy and to make it fast. >> And speaking of fast, that's one of the things I think the last year has taught us is that, real-time access to data is no longer a nice to have. It's really a competitive differentiator. Talk to me about how you enable customers to get access to the right data fast enough, to be able to do what so many companies say, and that is actually make data-driven decisions. >> Yeah, that's absolutely right. So, it really is a entire continuum. The first and most obvious thing that we do is we start with the user. So, if you're a user of data, you might have to hunt through a myriad of reports, thousands of tables in a database, hundreds of thousands of files in a data lake, and you might not know where to find your answer and you might have the best of intentions but if you don't have the time to go through all of those sources, the first thing you might do is, go ask your buddy down the hall. Now, if your buddy down the hall or your colleague over Zoom can't give you the time of day or can't answer your question quickly enough then you're not going to be able to use that data. So the first thing, and the most obvious thing that we do is we have the industry's best search experience and the industry's best browse experience. And if you think about that search experience, that's really fueled by our understanding of all of the data patterns in your data environment. We basically look at every search. We look at every log within a company's data environment to understand what it is that people are actually doing with the data. And that knowledge just like Google has page rank to help it inform which are the best results for a given webpage. We do the exact same thing with data. And so great search is the basis of what we do. Now, above and beyond that, there's a couple of other things that we do, but they all get to the point of getting to that end search experience and making that perfect so that people can then curate the data and leverage the data as easily as possible. >> Sounds like that's really kind of personalized based on the business, in terms of the search, looking at what's going on. Talk to me a little bit more about that, and how does that context help fuel innovation? >> Yeah. So, to build that context, you can't just do, historically and traditionally what's been done in the data management space. Lots of companies come to the data management world and they say, "Well, what we're going to do is we're going to hire... "We've got this great software. "But setting the software up is a journey. "It takes two to three to four years to set it up "and we're going to get an army of consultants "and everybody's going to go and assert quality of data assets "and measure what the data assets do "and figure out how the data assets are used. "And once we do all of that work, "then in four years we're going to get you to a response." The real key is not to have that context to be built, sort of through an army of consultants and an army of labor that frankly nine times out of 10 never gets to the end of the road. But to actually generate that context day one, by understanding what's going on inside of those systems and learning that by just observing what's happening inside of the company. And we can do that. >> Excellent. And as we've seen the acceleration in the last year of digital transformation, how much of that accelerant was an accelerator revelation putting this service forward and what are customers saying so far? >> Yeah, it's been incredible. I mean, what we've seen in our existing accounts is that, our expansions have gone up by over 100% year over year with the kind of crisis in place. Obviously, you would hypothesize that these catalogs, these, sort of accessibility and search tools and data in general, would be leveraged more when all of us are virtual and all of us can't talk to each other. But, it's been amazing to see that we've found that that's actually what's happening. People are actually using data more. People are actually searching for data more. And that experience and bringing that to our customers has been a huge focus of what we're trying to do. So we've seen the pandemic, in many cases obviously been bad for many people but for us it's been a huge accelerant of customers using our product. >> Talk to me about Alation with AWS. What does that enable your customers to achieve that they maybe couldn't necessarily do On-Prem? >> Yeah, so, customers obviously don't really care anymore, or as much as they used to, about managing the software internally. They just want to be able to, get whatever they need to get done and move forward with their business. And so by leveraging our partnership with AWS, one, we've got elastic compute capability. I think that's obviously, something that they bring to the table, better than perhaps any other in the market. But much more fundamentally, the ability to stand up Alation and get it going, now means that all you have to do is go to the AWS Marketplace or call up an Alation rep. And you can, within a matter of minutes, get an Alation instance that's up and running and fit for purpose for what you need. And that capability is really quite powerful because, now that we have that elasticity and the speed of deployment, customers can realize the value, so much more quickly than they otherwise might've. >> And that speed is absolutely critical as we saw a lot last year that was the difference between the winners and those that were not going to make it. Talk to me a little bit about creating a data culture. We talk about that a lot. It's one thing to talk about it, it's a whole other thing to put it in place, especially for legacy institutions that have been around for a while. How do you help facilitate the actual birth of a data culture? >> Yeah, I mean, I think we view ourselves as a technology, as a catalyst, to our best customers and our best customer champions. And when we talk to chief data officers and when we talk to data leaders within various organizations that we service, organizations like Pfizer, organizations like Salesforce, organizations like Cisco, what they often tell me is, "Look, we've got to build products faster. "We've got to move at the speed and the scale "of all of the startups that are nipping at our heels. "And how do we do that? "Well, we've got to empower our people "and the way that we empower our people "is by giving them context. "And we need to give them the data "to make the right decisions, "so that they can build those products "and move faster than they ever might've." Now those are amazing intentions but those same leaders also come and say, "I've just been mired in risk "and I've been mired in compliance, "and I've been mired in "doing all of these data janitorial projects. "And it's really hard for me to get "on the offense with data. "It's really hard for me to get proactive with data." And so the biggest thing that we do, is we just help companies be more proactive, much more easily, because what they're able to do, is they're able to leave a lot of that janitorial work, lead a lot of that discovery work, lead a lot of that curation work to the software. And so what they get to focus on is, how is it that I can then drive change and drive behavioral change within my organizations so that people have the right data at their disposal. And that's really the magic of the technology. >> So I was reading the "Alation State of Data Culture Report" that was just published a few weeks ago. This is this quarterly assessment that Alation does, looking at the progress that enterprises have made in creating this data culture. And the number that really struck out at me was 87% of respondents say, data quality issues are a barrier to successful implementation of AI in their organizations. How can Alation help them solve that problem? >> Yeah, I think the first is, whenever you've got a problem, the first thing you've got to do is acknowledge that you've got a problem. And a lot of the time people, leaders will often jump to AI and say, "well, hey, everybody's talking about AI. "The board level conversation is AI. "McKinsey is talking about AI, let's go do some AI." And that sounds great in theory. And of course we all want to do that more, but the reality is that many of these projects are stymied by the basic plumbing. You don't necessarily know where the data's coming from. You don't know if people have entered it properly in the source systems or in the systems that are online. Those data often get corrupted in the transformation processes or the processes themselves don't run appropriately. And so you don't have transparency. You don't have any awareness of what people are doing, what people are using, how the data is actually being manipulated from step to step, what that data lineage is. And so that's really where we certainly help many of our customers by giving them transparency and an understanding of their data landscape. Ironically, what we find is that, data leaders are super excited to get data to the business but they often don't themselves have the data to understand how to manage the data itself. >> Wow, that's a conundrum. Let's talk about customers because I was looking on the website and there's some pretty big metrics-based business outcomes that Alation is helping customers drive. I wanted to kind of pick through some examples from your perspective. First one is 364% ROI. Second one is 70% less time for analysts to complete projects. Workforce productivity is huge. Talk to me about how Alation is helping customers achieve business outcomes like that. >> Yeah, so if you think about a typical analytical project you would think that most of the time is spent inside of the analytical tool, inside of your Excel, inside of your Tableau, that where you're thinking about the data and you're analyzing it, you're thinking deep thoughts. And you're trying to hypothesize you're trying to understand. But the reality is going back to the data quality issue that most of the time is spent with figuring out which are the right datasets. Because at one of our customers, for example, there were 4,000 different types of customer transaction datasets, that spoke to the exact same data. Which data set do I actually use out of a particular database? And then once I figured out which ones to use, how do I construct the appropriate query and assumptions in order to be able to get the data into a format that makes sense to me. Those are the kinds of things that most analysts and data scientists struggle with. And what we do is we help them by not having them reinvent the wheel. We allow them to figure out what the right dataset is fast, how to manipulate it fast, so that they can focus most of their time on doing that end analytical work. And that's where all the ROI or a lot of the ROI is coming from because they don't know how to reinvent the wheel. They can do the work and they can move on with the much faster business decision which means that that business moves significantly faster. And so what we find is that for these very highly priced resources, some data scientists who make 200, 300, $400,000 fully load it for a company, those people can do their job 74% faster which means they can get not only the answer faster but they can get many more tasks done, for over a given period of time. >> Well, that just opens up a potential suite of benefits that the organization will achieve, not just getting the analyst productivity cranked up in a big way, but also allowing your organization to be more agile which many organizations are striving to be. to be able to identify new products, new services, what's happening, especially, in a changing chaotic environment like we've been living in the last year. >> Yeah, absolutely. And they also can learn... Not only can they help themselves figure out what new products to launch, but they can also help themselves figure out where their risks happen to be, and where they need to comply, because it could be the case that analysts are using datasets that they ought not to be using or the businesses using the data incorrectly. And so you can find both the patterns but also the anti-patterns, which means that you're not only moving faster, but you're moving forward with less risk. And so we've seen so many failures with data governance, regimes, where people have tried to assert the quality of data and figure out the key data elements and develop a business glossary. And there's that great quote, "I wanted data governance but all I got is a data glossary." That all happens because, they just don't have enough time in the day to do the value added work. They only have enough time in the day to start doing the data cleaning and all of the janitorial work that we, as a company, really strive to allow them to completely eliminate. >> So wrapping things up here, Alation Cloud Service. Tell me about when it's available, how can customers get it? >> So it's available today, which is super exciting. Customers can get it either through the AWS Marketplace or by calling your Alation representative. You can do that coming to our website. And that's super easy to do and getting a demo and moving forward. But we try to make it as easy as possible. And we really want to get out of the way, of allowing people to have a seamless frictionless experience and are super excited to have this cloud service that allows them to do that, even faster than they were able to do before. >> And we all know how important that speed is. Well, Satyen, congratulations on the announcement of Alation Cloud Service. We appreciate you coming on here and sharing with us the news and really what's in it for the customers. >> Thank you, Lisa. It's been phenomenal catch up and great seeing you. >> Likewise. For Satyen Sangani, I'm Lisa Martin. You're watching this "CUBE Conversation." (soft music)

>> Narrator: From theCUBE studios in Palo Alto, in 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 coming to you today from our Palo Alto studios with theCUBE conversation, talking about data, and we're excited to have our next guest. He's been on a number of times, many times, CUBE alum, really at the forefront of helping companies and customers be more data centric in their activities. So we'd like to welcome onto the show Satyen Sangani. He is the co founder and CEO of Alation. Satyen, great to see you. >> Great to see you, Jeff. It's good to see you again in this new world, a new format. >> It is a new world, a new format, and what's crazy is, in March and April we were talking about this light switch moment, and now we've just turned the calendar to October and it seems like we're going to be doing this thing for a little bit longer. So, it is kind of the new normal, and even I think when it's over, I don't think everything's going to go back to the way it was, so here we are, but you guys have some exciting news to announce, so let's just jump to the news and then we'll get into a little bit more of the nitty gritty. So what do you got coming out today, right? >> Yeah its so. >> What we are announcing today is basically Alation 2020, which is probably one of the biggest releases that I've been with, that we've had since I've been with the company. We with it are releasing three things. So in some sense, there's a lot of simplicity to the release. The first thing that we're releasing is a new experience around what we call the business user experience, which will bring in a whole new set of users into the catalog. The second thing that we're announcing is basically around Alation analytics and the third is around what we would describe as a cloud-native architecture. In total, it brings a fully transformative experience, basically lowering the total cost of getting to a data management experience, lower and data intelligent experience, much lower than previously had been the case. >> And you guys have a really simple mission, right? You're just trying to help your customers be more data, what's the right word? Data centric, use data more often and to help people actually make that decision. And you had an interesting quote in another interview, you talked about trying to be the Yelp for information which is such a nice kind of humanizing way to think about it because data isn't necessarily that way and I think, you mentioned before we turned on the cameras, that for a lot of people, maybe it's just easier to ignore the data. If I can just get the decision through, on a gut and intuition and get onto my next decision. >> Yeah, you know it's funny. I mean, we live in a time where people talk a lot about fake news and alternative facts and our vision is to empower a curious and rational world and I always smile when I say that a little bit, because it's such a crazy vision, right? Like how you get people to be curious and how do you get people to think rationally? But you know, to us, it's about one making the data really accessible, just allowing people to find the data they need when and as they want it. And the second is for people to be able to think scientifically, teaching people to take the facts at their disposal and interpret them correctly. And we think that if those two skills existed, just the ability to find information and interpret it correctly, people can make a lot better decisions. And so the Yelp analogy is a perfect one, because if you think about it, Yelp did that for local businesses, just like Amazon did it for really complicated products on the web and what we're trying to do at Alation is, in some sense very simple, which is to just take information and make it super usable for people who want to use it. >> Great, but I'm sure there's the critics out there, right? Who say, yeah, we've heard this before the promise of BI has been around forever and I think a lot of peoples think it just didn't work whether the data was too hard to get access to, whether it was too hard to manipulate, whether it was too hard to pull insights out, whether there's just too much scrubbing and manipulating. So, what is some of the secret sauce to take? What is a very complex world? And again and you got some very large customers with some giant data sets and to, I don't want to say humanize it, but kind of humanize it and make it easier, more accessible for that business analyst not just generally, but more specifically when I need it to make a decision. >> Yeah I mean, it's so funny because, making something, data is like a lot of software death by 1000 cuts. I mean you look at something from the outside and it looks really, really, really simple, but then you kind of dwell into any problem and that can be CRM something like Salesforce, or it can be something like service now with ITSM, but these are all really, really complicated spaces and getting into the depths and the detail of it is really hard. And data is really no different, like data is just the sort of exhaust from all of those different systems that exist inside of your company. So the detail around the data in your company is exhaustingly minute. And so, how do you make something like that simple? I think really the biggest challenge there is progressively revealing complexity, right? Giving people the right amount of information at the right amount of time. So, one of the really clever things that we do in this business user experience is we allow people to search for and receive the information that's most relevant to them. And we determined that relevance based upon the other people in the enterprise that happen to be using that data. And we know what other people are using in that company, because we look at the logs to understand which data sources are used most often, and which reports are used most often. So right after that, when you get something, you just see the name of the report and it could be around the revenues of a certain product line. But the first thing that you see is who else uses it. And that's something that people can identify with, you may not necessarily know what the algorithm was or what the formula might be, how the business glossary term relates to some data model or data artifact, but you know the person and if you know the person, then you can trust the information. And so, a lot of what we do is spend time on design to think about what is it that a person expects to see and how do they verify what's true. And that's what helps us really understand what to serve up to somebody so that they can navigate this really complicated, relevant data. >> That's awesome, cause there's really a signal to noise problem, right? And I think I've heard you speak before. >> Yeah >> And of course this is not new information, right? There's just so much data, right? The increasing proliferation of data. And it's not that there's that much more data, we're just capturing a lot more of it. So your signal to noise problem just gets worse and worse and worse. And so what you're talking about is really kind of helping filter that down to get through a lot of that, a lot of that noise, so that you can find the piece of information within the giant haystack. That is what you're looking for at this particular time in this particular moment. >> Yeah and it's a really tough problem. I mean, one of the things that, it's true that we've been talking about this problem for such a long time. And in some instance, if we're lucky, we're going to be talking about it for a lot longer because it used to be that the problem was, back when I was growing up, you were doing research on a topic and you'd go to the card catalog and you'd go to the Dewey decimal system. And in your elementary school or high school library, you might be lucky if you were to find, one, two or three books that map to the topic that you were looking for. Now, you go to Google and you find 10,000 books. Now you go inside of an enterprise and you find 4,000 relational database tables and 200 reports about an artifact that you happened to be looking for. And so really the problem is what do I trust? And what's correct and getting to that level of accuracy around information, if there's so much information out there is really the big problem of our time and I think, for me it's a real privilege to be able to work on it because I think if we can teach people to use information better and better then they can make better decisions and that can help the world in so many different. >> Right, right, my other favorite example that everybody knows is photographs, right? Back when you only got 24 and a roll and cost you six bucks to develop it. Those were pretty special and now you go buy a fancy camera. You can shoot 11, 11 frames a second. You go out and shoot the kids at the soccer game. You come home with 5,000 photos. How do you find the good photo? It's a real, >> Yeah. >> It's a real problem. If you've ever faced something like that, it's kind of a splash of water in the face. Like where do I even begin? But the other piece that you talk about a lot, which is slightly different but related is context, and in favorite concept, it's like 55, right? That's a number, but if you don't have any context for that number, is it a temperature? Is it cold inside the building? Is it a speed? Is it too slow on i5? Or is it fast because I'm on a bicycle going down a Hill and without context data is just, it's just a number. It doesn't mean anything. So you guys really by adding this metadata around the data are adding a lot more contextual information to help figure out kind of what that signal is from the noise. >> Yap, you'll get facts from anywhere, right? Like, you're going to have a Hitchcock, you've got a 55 or 42, and you can figure out like what the meaning of the universe is and apparently the answer is 42 and what does that mean? It might mean a million different things and that, to me, that context is the difference between, suspecting and knowing. And there's the difference between having confidence and basically guessing. And I think to the extent that we can provide more of that over time, that's, what's going to make us, an ever more valuable partner to the customers that we satisfy today. >> Right, well, I do know why 42 is always the answer 'cause that's Ronnie Lot and that's always the answer. So, that one I know that's an easy one. (both chuckles) But it is really interesting and then you guys just came out. I heard Aaron Kalb on, one of your co-founders the other day and we talked about this new report that you guys have sponsored the Data Culture Report and really, putting some granularity on a Data Culture Index and I thought it was pretty interesting and I'm excited that you guys are going to be doing this, longitudinally because whether you do or do not necessarily agree with the method, it does give you a number, It does give you a score, It's a relatively simple formula. And at least you can compare yourself over time to see how you're tracking. I wonder if you could share, I mean, the thing that jumps out right off the top of that report is something we were talking about before we turned the cameras on that, people's perception of where they are on this path doesn't necessarily map out when you go bottoms up and add the score versus top down when I'm just making an assessment. >> Yeah, it's funny, it's kind of the equivalent of everybody thinks they're an above average driver or everybody thinks they're above average in terms of obviously intelligence. And obviously that mathematically is not possible or true, but I think in the world of data management, we all talk about data, we all talk about how important it is to use data. And if you're a data management professional, you want people in your company to use more data. But ironically, the discipline of data management doesn't actually use a lot of data itself. It tends to be a very slow methodical process driven gut oriented process to develop things like, what data models exist and how do I use my infrastructure and where do I put my data and which data quality is best? Like all of those things tend to be, somewhat heuristic driven or gut driven and they don't have to be and a big part of our release actually is around this product called Alation Analytics. And what we do with that product is really quite interesting. We start measuring elements of how your organization uses data by team, by data source, by use case. And then we give you transparency into what's going on with the data inside of your landscape and eco-system. So you can start to actually score yourself both internally, but also as we reveal in our customer success methodology against other customers, to understand what it is that you're doing well and what it is that you're doing badly. And so you don't need necessarily to have a ton of guts instinct anymore. You can look at the data of yourselves and others to figure out where you need to improve. And so that's a pretty exciting thing and I think this notion that says, look, you think you're good, but are you really good? I mean, that's fundamental to improvement in business process and improvement in data management, improvement in data culture fundamentally for every company that we work with. >> Right, right and if you don't know, there's a problem, and if you're not measuring it, then there's no way to improve on it, right? Cause you can't, you don't know, what you're measuring is. >> Right. >> But I'm curious of the three buckets that you guys measured. So you measured data search and discovery was bucket number one, data literacy, you know what you do once you find it and then data governance in terms of managing. It feels like that the search and discovery, which is, it sounds like what you're primarily focused on is the biggest gap because you can't get to those other two buckets unless you can find and understand what you're looking for. So is that JIve or is that really not problem, is it more than manipulation of the data once you get it? >> Yeah, I mean we focus really. We focus on all three and I think that, certainly it's the case that it's a virtuous cycle. So if you think about kind of search and discovery of data, if you have very little context, then it's really hard to guide people to the right bit of information. But if I know for example that a certain data is used by a certain team and then a new member of that team comes on board. Then I can go ahead and serve them with exactly that bit of data, because I know that the human relationships are quite tight in the context graph on the back end. And so that comes from basically building more context over time. Now that context can come from a stewardship process implemented by a data governance framework. It can come from, building better data literacy through having more analytics. But however, that context is built and revealed, there tends to be a virtuous cycle, which is you get more, people searching for data. Then once they've searched for the data, you know how to necessarily build up the right context. And that's generally done through data governance and data stewardship. And then once that happens, you're building literacy in the organization. So people then know what data to search for. So that tends to be a cycle. Now, often people don't recognize that cycle. And so they focus on one thing thinking that you can do one to the exclusion of the others, but of course that's not the case. You have to do all three. >> Great and I would presume you're using some good machine, Machine Learning and Artificial Intelligence in that process to continue to improve it over time as you get more data, the metadata around the data in terms of the usage and I think, again I saw in another interview there talking about, where should people invest? What is the good data? What's the crap data? what's the stuff we shouldn't use 'cause nobody ever uses it or what's the stuff, maybe we need to look and decide whether we want to keep it or not versus, the stuff that's guiding a lot of decisions with Bob, Mary and Joe, that seems to be a good investment. So, it's a great application of applied AI Machine Learning to a very specific process to again get you in this virtuous cycle. That sounds awesome. >> Yeah, I know it is and it's really helpful to, I mean, it's really helpful to think about this, I mean the problem, one of the biggest problems with data is that it's so abstract, but it's really helpful to think about it in just terms of use cases. Like if I'm using a customer dataset and I want to join that with a transaction dataset, just knowing which other transaction datasets people joined with that customer dataset can be super helpful. If I'm an analyst coming in to try to answer a question or ask a question, and so context can come in different ways, just in the same way that Amazon, their people who bought this product also bought this product. You can have all of the same analogies exist. People who use this product also use that product. And so being able to generate all that intelligence from the back end to serve up simple seeming experience on the front end is the fun part of the problem. >> Well I'm just curious, cause there's so many pieces of this thing going on. What's kind of the, aha moment when you're in with a new customer and you finish the install and you've done all the crawling and where all the datasets are, and you've got some baseline information about who's using what I mean, what is kind of the, Oh, my goodness. When they see this thing suddenly delivering results that they've never had at their fingertips before. >> Yeah, it's so funny 'cause you can show Alation as a demo and you can show it to people with data sets that are fake. And so we have this like medical provider data set that, we've got in there and we've got a whole bunch of other data sets that are in there and people look at it and interestingly enough, a lot of time, they're like, Oh yeah, I can kind of see it work and I can kind of like understand that. And then you turn it on against their own data. The data they have been using every single day and literally their faces change. They look at the data and they say, Oh my God, like, this is a dataset that Steven uses, I didn't even know that Steven thought that this data existed and, Oh my God, like people are using this data in this particular way. They shouldn't be using that data at all, Like I thought I deprecated that dataset two years ago. And so people have all of these interesting insights and it's interesting how much more real it gets when you turn it on against the company's systems themselves. And so that's been a really fun thing that I've just seen over and over again, over the course of multiple years where people just turn on the cup, they turn on the product and all of a sudden it just changes their view of how they've been doing it all along. And that's been really fun and exciting. >> That's great yeah, cause it means something to them, right? It's not numbers on a page, It's actually, it's people, it's customers, it's relationships, It's a lot of things. That's a great story and I'm curious too, in that process, is it more often that they just didn't know that there were these other buckets of reports and other buckets of data or was it more that they just didn't have access to it? Or if they did, they didn't really know how to manipulate it or to integrate it into their own workflow. >> Yeah, It's kind of funny and it's somewhat role dependent, but it's kind of all of the above. So, if you think about it, if you're a data management professional, often you kind of know what data sources might exist in the enterprise, but you don't necessarily know how people are using the data. And so you look at data and you're like, Oh my God, I can't believe this team is using this data for this particular purpose. They shouldn't be doing that. They should be using this other data set. I deprecated that data set like two years ago. And then sometimes if you're a data scientist, you're you find, Oh my gosh, there's this new database that I otherwise didn't realize existed. And so now I can use that data and I can process that for building some new machine learning algorithms. In one case we've had a customer where they had the same data set procured five different times. So it was a pure, it was a data set that cost multiple hundreds of thousands of dollars. They were spending $2 million overall on a data set where they could have been spending literally one fifth of that amount. And then you had a sort of another case finally, where you're basically just looking at it and saying, Hey, I remember that data set. I knew I had that dataset, but I just don't remember exactly where it was. Where did I put that report? And so it's exactly the same way that you would use Google. Sometimes you use it for knowledge discovery, but sometimes you also use it for just remembering the thing you forgot. >> Right but, but the thing, like I remember when people were trying to put Google search in that companies just to find records not necessarily to support data efforts and the knock was always, you didn't have enough traffic to drive the algorithm to really have effective search say across a large enterprise that has a lot of records, but not necessarily a lot of activity. So, that's a similar type of problem that you must have. So is it really extracting that extra context of other people's usage that helps you get around kind of that you just don't have a big numbers? >> Yeah, I mean that kind of is fundamentally the special sauce. I mean, I think a lot of data management has been this sort of manual brute force effort where I get a whole bunch of consultants or a whole bunch of people in the room and we do this big documentation session. And all of a sudden we hope that we've kind of, painted the golden gate bridge is at work. But, knowing that three to six months later, you're going to have to go back and repaint the golden gate bridge overall all over again, if not immediately, depending on the size and scale of your company. The one thing that Google did to sort of crawl the web was to really understand, Oh, if a certain webpage was linked to super often, then that web page is probably a really useful webpage. And when we crawled the logs, we basically do the exact same thing. And that's really informed getting a really, really specific day one view of your data without having to have a whole bunch of manual effort. And that's been really just dramatical. I mean, it's been, it's allowed people to really see their data very quickly and new different ways and I think a big part of this is just friction reduction, right? We'd all love to have an organized data world. We'd love to organize all the information in a company, but for anybody has an email inbox, organizing your own inbox, let alone organizing every database in your company just seems like a specificity in effort. And so being able to focus people on what's the most important thing has been the most important thing. And that's kind of why we've been so successful. >> I love it and I love just kind of the human factors kind of overlay, that you've done to add the metadata with the knowledge of who is accessing these things and how are they accessing it. And the other thing I think is so important Satyen is, we talk about innovation all the time. Everybody wants more innovation and they've got DevOps so they can get software out faster, et cetera, et cetera. But, I fundamentally believe in my heart of hearts that it's much more foundational than that, right? That if you just get more people, access to more information and then the ability to manipulate and clean knowledge out of that information and then actually take action and have the power and the authority to take action. And you have that across, everyone in the company or an increasing number of people in the company. Now suddenly you're leveraging all those brains, right? You're leveraging all that insight. You're leveraging all that kind of First Line experience to drive kind of a DevOps type of innovation with each individual person, as opposed to, kind of classic waterfall with the Chief Innovation Officer, Doing PowerPoints in his office, on his own time. And then coming down from the mountain and handing it out to everybody to go build. So it's a really a kind of paradox that by adding more human factors to the data, you're actually making it so much more usable and so much more accessible and ultimately more valuable. >> Yeah, it's funny we, there's this new term of art called data intelligence. And it's interesting because there's lots of people who are trying to define it and there's this idea and I think IDC, IDC has got a definition and you can go look it up, but if you think about the core word of intelligence, it basically DevOps down to the ability to acquire information or skills, right? And so if you then apply that to companies and data, data intelligence then stands to reason. It's sort of the ability for an organization to acquire, information or skills leveraging their data. And that's not just for the company, but it's for every individual inside of that company. And we talk a lot about how much change is going on in the world with COVID and with wildfires here in California. And then obviously with the elections and then with new regulations and with preferences, cause now that COVID happened everybody's at home. So what products and what services do you have to deliver to them? And all of this change is, basically what every company has to keep up with to survive, right? If capitalism is creative destruction, the world's getting destroyed, like, unfortunately more often than we'd like it to be,. >> Right. >> And so then you're say there going, Oh my God, how do I deal with all of this? And it used to be the case that you could just build a company off of being really good at one thing. Like you could just be the best like logistics delivery company, but that was great yesterday when you were delivering to restaurants. But since there are no restaurants in business, you would just have to change your entire business model and be really good at delivering to homes. And how do you go do that? Well, the only way to really go do that, is to be really, really intelligent throughout your entire company. And that's a function of data. That's a function of your ability to adapt to a world around you. And that's not just some CEO cause literally by the time it gets to the CEO, it's probably too late. Innovations got to be occurring on the ground floor. And people have got to repackage things really quickly. >> I love it, I love it. And I love the other human factor that we talked about earlier. It's just, people are curious, right? So if you can make it easy for them to fulfill their curiosity, they're going to naturally seek out the information and use it versus if you make it painful, like a no fun lesson, then people's eyes roll in and they don't pay attention. So I think that it's such an insightful way to address the problem and really the opportunity and the other piece I think that's so different when you're going down the card catalog analogy earlier, right? Is there was a day when all the information was in that library. And if you went to the UCLA psych library, every single reference that you could ever find is in that library, I know I've been there, It was awesome, but that's not the way anymore, right? You can't have all the information and it's pulling your own information along with public information and as much information as you can. where you start to build that competitive advantage. So I think it's a really great way to kind of frame this thing where information in and of itself is really not that valuable. It's about the context, the usability, the speed of these ability and that democratization is where you really start to get these force multipliers and using data as opposed to just talking about data. >> Yeah and I think that that's the big insight, right? Like if you're a CEO and you're kind of looking at your Chief Data Officer or Chief Data and Analytics Officer. The real question that you're trying to ask yourself is, how often do my people use data? How measurable is it? Like how much do people, what is the level at which people are making decisions leveraging data and that's something that, you can talk about in a board room and you can talk about in a management meeting, but that's not where the question gets answered. The question gets really answered in the actual behaviors of individuals. And the only way to answer that question, if you're a Chief Analytics Officer or somebody who's responsible for data usage within the company is by measuring it and managing it and training it and making sure it's a part of every process and every decision by building habit and building those habits are just super hard. And that's, I think the thing that we've chosen to be sort of the best in the world at, and it's really hard. I mean, we're still learning about how to do it, but, from our customers and then taking that knowledge and kind of learning about it over time. >> Right, well, that's fantastic. And if it wasn't hard, it wouldn't be valuable. So those are always the best problems to solve. So Satyen, really enjoyed the conversation. Congratulations to you and the team on the new release. I'm sure there's lots of sweat, blood and tears that went into that effort. So congrats on getting that out and really great to catch up. Look forward to our next catch up. >> You too Jeff, It's been great to talk. Thank you so much. >> All right, take care. All righty Satyen and I'm Jeff, you're watching theCUBE. We'll see you next time. Thanks for watching. (ethereal music)

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in our Palo Alto studios today for theCUBE conversation. We're talking about data. We're always talking about data and it's really interesting. You know we like to go out and get you the first person insight from the people that start the companies, run the companies, the practitioners and, and, and get the insight directly from them. We also like to go out and get original research and hear from original research. And this is a great opportunity to hear from both. So we're excited to have, and welcome back into the studio. He's Aaron Kalb. He's the co founder of Alation, many time CUBE alumni. Aaron. Great to see you. >> Yeah, thanks for having me. It's good to be here. >> Yeah, it's very cool. But today it's a special, a special thing. We've never done this before with you. You guys are releasing a brand new report called, the Alation State of Data Culture Report. So really interesting report. A lot of great information that we're going to dig in here for the next few minutes. But before we do, tell us kind of the history of this report. This is a, the kind of the inaugural release. What was kind of behind it, why did you guys do this? And give us a little background before we get into the details. >> Absolutely. So, yes, that's exactly right. It's debuting today that we plan to kind of update this research quarterly we going to see the trends over time. And this emerged because, you know, I, part of my job, I talk to chief data officers and chief analytics officers across our customer base and prospects. And I keep hearing anecdotally over and over that establishing a data culture, is often the number one priority for these data leaders and for these organizations. And so we wanted to really say, can we quantify that? Can we agree upon a definition of data culture? And can we create sort of a simple yardstick to more objectively measure where organizations are on this sort of data maturity curve to get it into culture. >> Right. I love it. So you created this data, data index right? The data culture index. And, and I think it's important to look at methodology. I think people, a lot of times go right to the results on reports before talking about the methodologies. And let's talk about the methodologies cause we're supposed to be talking about data, right? So you talked to 300, some odd executives, correct. And I think it's really interesting and you broke it down into three kind of buckets of data literacy, if you will. Data search and discovery, number one, data, two kind of literacy in terms of their ability to work with the data. And then the third bucket is really data governance. And then in, in the form ABCD, you gave him a four point score and basically, are they doing it well? Are they doing it in the majority of the time? Are they doing it about half, they got one or they got a zero and you get this four point scale and you end up with a 12 point scale which we're all familiar with from, from school, from an A to an, A minus and B, et cetera. Just dig it a little bit on those three categories and how you chose those. So the first one again is kind of the data search and discovery, you know can they find it and then their competency, if you will and then a governance and compliance. Kind of dig into each of those three buckets a little bit. >> For sure. So, so the, the end goal in data culture, is to have an organization in which data is valued and decisions are made based on data and evidence, right? Versus a culture in which we go with the highest paid person's opinion or what we did last quarter or any of these other ways things get done. And so the idea is to make that possible, as you said you've to be able to find the data when you need it. That's the data search and discovery. You've to be able to interpret that data correctly and draw valid conclusions from it. And that's a data literacy, excuse me. And both of those are contingent upon having data governance in place. So that data is well-defined and has high data quality, as well as other aspects, so that it is possible to find it and understand it properly. >> Right. And what are the things too that I think is really important that we call that, and again, we're going to dive into the details, is your perceived execution versus the reported execution by the people that are actually providing data. And I think you've found and you've highlighted on specific slides that you know, there's not necessarily a match there. And sometimes that you know, what you perceive is happening, isn't necessarily what's happening when you go down and query the people in the field. So really important to come up with a number. And I think a, I think you said this is going to be an ongoing thing over a period of time. So you kind of start to see longitudinal changes in these organizations. >> Absolutely. And we're very excited to see those, those trends over time. But even at the outset is this you know, very striking effect emerges which is, as you said, if we ask one of these you know, 300 data leaders, you know, all around the world actually, you know, if we ask, how is the data culture at your company overall, and this is very broad general top down way and have them graded on the sort of SaaS scale. You know, we get results where there's a large gap between kind of that level of maturity and what emerges in a bottom up methodology excuse me, in which you ask about, you know governance and literacy and, and such kind of by department and in a more bottom up way. And so we do see that that, you know, it can be helpful, even for data people to have a, a more granular metric and framework for quantifying their progress. >> Right? Let's jump into some of the results. It's, it's a fascinating, they're kind of all over the map, but there's some definite trends. One of the trends you talked about is that there's a lot of questions on the quality of the data. But that's a real inhibitor to people. Whether that suspicion is because it's not good data. And I don't know, this question for you, is, is, do they think it's not relevant to the decision that's being made? Is it an incomplete data set or the wrong data set? It seems to be that keeps coming up over and over about, decision-makers not necessarily having confidence in the data. What, can you share a little bit more color around that? >> Yeah, it's quite interesting actually. So what we find is that 90%. So 90 people, 10 executives (indistinct) to question the data sometimes often or always. But the part that's maybe disappointing or concerning is the two thirds of executives are believed to ignore the data and make a decision kind of pushing the data aside which is really quite striking when you think about it, why have all this data, if more often than not you're sort of disregarding it to make your final answer. And so you're absolutely correct when we dug into why, what are the reasons behind pushing it aside. Data quality was number one. And I think it is a question of, Oh, is the data inaccurate? Is it out of date, these sort of concerns sort of we, we hear from customers and prospects. But as we dig in deeper in the survey results, excuse me, we, we see some other reasons behind that. One is a lack of collaboration between the data analytics folks and the business folks. And so there's a question of, I don't know exactly where this data came from or to your point kind of how it was produced. What was the methodology? How was it sourced? And maybe because of that disconnect is a lack of trust. So trust really is the ultimate I think, failure to having data culture really take root. >> Right? And it's trust in this trust, as you said, not only in the data per se, the source of the data, the quality of the data, the relevance of the data but also the people who are providing you with the data. And obviously you get, you get some data sets. Sometimes you didn't get other data sets. So, that's really I'm a little bit disconcerting. The other thing I thought was kind of interesting is, it seems to be consistent that the, the primary reason that people are using big data projects is around operations and operations efficiency, a little bit about compliance, but, you know, it's interesting we had you on at the MIT CDOIQ, Chief Data Information Officer quality symposium, and you talked about the goodness of people moving from kind of a defensive posture to an offensive posture, you know using data in terms of product development and innovation. And, and what comes across in this survey is that's kind of down the list behind you know, kind of operational efficiency. We're seeing a little bit of governance and regulation but the, the quest for data as a tool for innovation, didn't really shine through in this report. >> Well, you know, it's very interesting. It depends whether you look at the aggregate level or you break things down a little bit more. So one thing we did after we got that zero to 12 scale on the data culture index or DCI, is it actually, we were able to break it down into thirds. And among the sort of bottom third, it has the least well-established data culture by this yardstick. We've found that governance and regulatory compliance, was the number one application of data. But among the top third of respondents, we actually found the opposite where things like providing a great customer experience, doing product innovation, those sort of things actually came to the fore and governance fell behind. So I think there is this curve where, It's table stakes to get the sort of defense side of data figured out. And then you can move on to offense in using data to make your organization meet its meet its other goals. >> Right. Right. And then I wanted to get your take on kind of the democratization of data, right? This is a, this is a trend that's been going on, and really, I think you said before you know, your guys' whole mission is to empower curious and rational world to give people the ability to ask the right questions have the right data and get the right answer. So, you know, we've seen democratization in terms of the access to the data, the access to the tools, the ability to do something with the data and the tool, and then the actual authority to execute business decision based on that. The results on that seem a little bit split here because a lot of the problems seem to be focused on leadership, not necessarily taking a data based decision move, but on the good hand a lot of people trying to break down data silos and make data more accessible for a larger group of people. So that more people in the organization are making data based decisions. This seems kind of like this little bit of a bifurcation between the C suite and everybody else trying to get their job done. >> Absolutely. There's always this question of you know, sort of the, that organizational wide initiative and then what's happening on the ground. One thing we saw that was very heartening and aligns with our customers index success, is a real emphasis being placed on having data governance and data context and data literacy factors sort of be embedded at the point of use. To not expecting people, to just like take a course and look things up and kind of end up with their workflow to be able to use data quickly and accurately and, and interpret it in varied ways. So that was really exciting to see as, as, as a initiative. It sort of bridges that gap along with initiatives to have more collaboration and integration between the data people and the business people. because really you know, they exist to serve one another. But in terms of the disconnect between the C suite and other parts of the org, there was a really interesting inverse correlation. Well, or maybe it's not interesting how you look at it, but basically, you know, when we talk to C level executives and ask, you know, does the C suite ignore data? Do they question data et cetera, those numbers came in lower than when we talked to, you know, senior director about the C suite right? It's sort of the farther you get, and there's a difference there, you know, from my perspective, I almost wonder whether that distance is actually is more objective viewpoint. And when you're in that role, it's hard to even see your cognitive biases and your tendency to ignore a data when it doesn't suit you. >> Right. Right. So there's, there's some other interesting things here. So one of them is, you know, kind of predictors, right? One of the whole reasons to do studies and collect data so that we can have some predictive ability. And, and it comes out here that the reporting structure is a strong predictor of a company's data tier structure. So, you know, there's the whole rise of the chief data officers and the chief analytics officer and the chief data and analytics officer and lots of conversations about those roles and what exactly are those roles and who do they report to. Your study finds a pretty compelling leading indicator that if that role is reporting to either the CEO or the executive board, which is often a one in the same person, that that's actually a terrific indicator of success in moving to a more data centric culture. >> That's absolutely correct. So we found that that top third of organizations on the data culture index were much more likely to have a chief data executive, a CDO, CAO or CDAO. In fact, they're more likely to have folks with the analytics in their title because in some organizations, data is thought to mean sort of raw data, infrastructural defense and analytics is sort of where it gets you know, infused into business processes and value. But certainly that top third is much more likely to have the chief data executive reporting into the executive board or CEO when the highest ranking data executive is under the CIO or some other part of the organization, those orgs tend to score a far lower on the DCI. >> Right. Right. So it's interesting, you know you're a really interesting guy even doing this for a while. You were at Siri before you were at Alation. So you have a really good feel for kind of what data can do and can't do and natural human or natural language processing and, and, and human voice interaction with these devices, a really interesting case study, and they can do a really good job within a small defined data set and instruction set, but they don't do necessarily so well once you kind of get outside how, how they're trained. And you've talked a lot about how metaphor shaped the way that we think and I know you and Dave talked about data oil and data lakes I don't want to necessarily go down that whole path but I do think it's important. And what came out of the study and the way people think about data. You know, there's a lot of conversation. How do you value data? Is data, you know it used to just be an expense that we had to buy servers to store the stuff we weren't sure what we ever did with it. So I wonder if there's any, you know, kind of top level metaphors level, kind of a thought or process or framing in the companies that you study that came out. maybe not necessarily in the top line data, but maybe in some of the notes that help define why some people, you know are being successful at making this transition and putting, you know kind of data out front of their decision processing versus data, either behind as a supporting thing or maybe data, I just don't have time with it or I don't trust it, or God knows where you got that, and this is not the data that I wanted. You know, was there any, you know, kind of tangental or anecdotal stuff that came out of this study that's more reflective of, of the softer parts of a data culture versus the harder parts in terms of titles and roles and, and, and job responsibilities. >> Yeah. It's a really interesting place to explore. I do think there's a, I don't want to make this overly simplistic group binary, but at the end of the day you know, like anything else within an organization, you can view data as a liability to say, okay, we have for example, you know, customer's names and phone numbers and passwords, and we just need to prevent an adverse event in which there's a leak or some sort of InfoSec problem that could cause, you know, bad press and fines and other negative consequences. And I think the issue there is if data's a liability, the most you know, the best case is that it's worth zero as opposed to some huge negative on your company's balance sheet. And, and I think, you know, intuitively, if you really want to prevent data misuse and data problems, one fail safe, but I think ultimately in its own way risky way to do that was just not collect any data, right. And not store it. So I think that the transition is to say, look data must be protected and taken care of that's step zero. But you know, it's really just the beginning and data is this asset that can be used to inform the huge company level strategic decisions that are made in annual planning at the board level, down to the millions of little decisions every day in the work of people in customer support and in sales and in product management and in, you know, various roles that just across industries. And I think once you have that, that shift, you know the upside is potentially, you know, unbounded. >> Right. And, and it just changes the way, the way you think. And suddenly instead of saying, Oh, data needs to be kind of hidden away, it's more like, Oh, people need to be trained on data use and empowered with data. And it's all about not if it's used or if it's misused but really how it's used and why it's used, what it's being used for to make a real impact. >> Right. Right. And it's funny when I just remember it being back in business school one of the great things that help teach is to think in terms of data, right. And you always have the infamous center consulting interview question, How many manhole covers are in Manhattan. Right. So, you know, to, to, to start to think about that problem from a data centric, point of view really gives you a leg up and, and even, you know where to start and how to attack those types of problems. And I thought it was interesting you know, talking about challenges for people to have a more data centric, point of view. It's interesting. The reports says, basically everybody said there's all kinds of challenges around data quality and compliance, and they had democratization. But the bottom companies, the bottom companies said that the biggest challenge was lack of buy in from company leadership. So I guess the good news bad news is that there's a real opportunity to make a significant change and get your company from the bottom third to a middle third or a top third, simply by taking a change in attitude about putting data in a much more central role in your decision making process. 'Cause all the other stuff's kind of operational, execution challenges that we all have, not enough people, blah, blah, blah. But in terms of attitude of leadership and prioritization, that's something that's very easy to change if you so choose. And really seems to be the key to unlock this real journey as opposed to the minutiae of a lot of the little details that that are a challenge for everybody. >> Absolutely. In your changing attitudes might be the easiest thing or the hardest thing depending on (indistinct). But I think you're absolutely right. The first step, which, which which could, maybe it should be easy, is admitting that you have a problem or maybe to put it more positively, realizing you have an opportunity. >> I love that. And then just again, looking at the top tier companies, the other thing that I thought was pretty interesting in this study is, I'm looking at it here, is getting champions in each of the operational segments. So rather than, I mean, a chief data officer is important and you know, somebody kind of at the high level to shepherd it in the executive suite, as we just discussed, but within each of the individual tasks and functions and roles, whether that's operations or customer service or product development or operational efficiency, you need some type of champion, some type of person, you know, banging the gavel, collecting the data, smoothing out the complexities, helping people get their thing together. And again, another way to really elevate your position on the score. >> Absolutely. And I think this idea of again, bridging between, you know, if data is centralized you have a chance to try to really get excellent practices within the data org. But even it becomes even more essential to have those ambassadors, people who are in the business and understand all the business context who can sort of make the data relevant, identify the key areas where data can really help, maybe demystify data and pick the right metaphors and the right examples to make it real for the people in their function. >> Right. Right. So Aaron has a lot of great stuff. People can go to the website at alation.com. I'm sure you'll have a link to this, a very prominently displayed, but, and they should and they should check it out and really think about it and think about how it applies to their own situation, their own department, company et cetera. I just wanted to give you the last word before we before we sign off, you know, kind of what was the most you know, kind of positive affirmation or not the most but one or two of the most outcome affirming outcomes of this exercise. And what were one or two of the things that were a little concerning or, you know, kind of surprises on the downside that, that came out of this research? >> Yeah. So I think one thing that was maybe surprising or concerning the biggest one is sort of where we started with that disconnect between, you know, what people would, say as an off the cuff overall assessment and the disconnect between that and what emerges when we go department by department and (indistinct) to be pillars of data culture from such a discovery to data literacy, to data governance. I think that disconnect, you know, should give one pause. I think certainly it should make one think, Hmm. Maybe I shouldn't look from 10,000 feet, but actually be a little more systematic. And considering the framework I use to assess data culture that is the most important thing to my organization. I think though, there's this quote that you move what you measure, just having this hopefully simple but not simplistic yardstick to measure data culture and the data culture index should help people be a little bit more realistic in their quantification and they track their progress, you know, quarter over quarter. So I think that's very promising. I think another thing is that, you know sometimes we ask, how long have you had this initiative? How much progress have you made? And it can sometimes seem like pushing a boulder uphill. Obviously the COVID pandemic and the economic impacts of that has been really tragic and really hard. You know, a tiny silver lining in that is the survey results showed that organizations have really observed a shift in how much they're using data because sometimes things are changing but it's like a frog in boiling water. You don't realize it. And so you just assume that the future is going to look like the recent past and you don't look at the data or you ignore the data or you miss parts of the data. And a lot of organizations said, you know COVID was this really troubling wake up call, but they could even after this crisis is over, producing enduring change which people were consulting data more and making decisions in a more data driven way. >> Yeah, certainly an accelerant that, that is for sure whether you wanted it, didn't want it, thought you had it at the time, didn't have time. You know COVID is definitely digital transformation accelerant and data is certainly the thing that powers that. Well again, it's the Alation State of Data Culture Report available, go check it at alation.com. Aaron always great to catch up and again, thank you for, for doing the work and supporting this research. And I think it's really important stuff. And it's going to be interesting to see how it changes over time. 'Cause that's really when these types of reports really start to add value. >> Thanks for having me, Jeff and I really look forward to discussing some of those trends as the research is completed. >> All right. Thanks a lot, Aaron, take care. Alright. He's Aaron and I'm Jeff. You're watching theCUBE, Palo Alto. Thanks for watching. We'll see you next time. (upbeat music)

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in our Palo Alto studios today for theCUBE conversation. We're talking about data. We're always talking about data and it's really interesting. You know we like to go out and get you the first person insight from the people that start the companies, run the companies, the practitioners and, and, and get the insight directly from them. We also like to go out and get original research and hear from original research. And this is a great opportunity to hear from both. So we're excited to have, and welcome back into the studio. He's Aaron Kalb. He's the co founder of Alation, many time CUBE alumni. Aaron. Great to see you. >> Yeah, thanks for having me. It's good to be here. >> Yeah, it's very cool. But today it's a special, a special thing. We've never done this before with you. You guys are releasing a brand new report called, the Alation State of Data Culture Report. So really interesting report. A lot of great information that we're going to dig in here for the next few minutes. But before we do, tell us kind of the history of this report. This is a, the kind of the inaugural release. What was kind of behind it, why did you guys do this? And give us a little background before we get into the details. >> Absolutely. So, yes, that's exactly right. It's debuting today that we plan to kind of update this research quarterly we going to see the trends over time. And this emerged because, you know, I, part of my job, I talk to chief data officers and chief analytics officers across our customer base and prospects. And I keep hearing anecdotally over and over that establishing a data culture, is often the number one priority for these data leaders and for these organizations. And so we wanted to really say, can we quantify that? Can we agree upon a definition of data culture? And can we create sort of a simple yardstick to more objectively measure where organizations are on this sort of data maturity curve to get it into culture. >> Right. I love it. So you created this data, data index right? The data culture index. And, and I think it's important to look at methodology. I think people, a lot of times go right to the results on reports before talking about the methodologies. And let's talk about the methodologies cause we're supposed to be talking about data, right? So you talked to 300, some odd executives, correct. And I think it's really interesting and you broke it down into three kind of buckets of data literacy, if you will. Data search and discovery, number one, data, two kind of literacy in terms of their ability to work with the data. And then the third bucket is really data governance. And then in, in the form ABCD, you gave him a four point score and basically, are they doing it well? Are they doing it in the majority of the time? Are they doing it about half, they got one or they got a zero and you get this four point scale and you end up with a 12 point scale which we're all familiar with from, from school, from an A to an, A minus and B, et cetera. Just dig it a little bit on those three categories and how you chose those. So the first one again is kind of the data search and discovery, you know can they find it and then their competency, if you will and then a governance and compliance. Kind of dig into each of those three buckets a little bit. >> For sure. So, so the, the end goal in data culture, is to have an organization in which data is valued and decisions are made based on data and evidence, right? Versus a culture in which we go with the highest paid person's opinion or what we did last quarter or any of these other ways things get done. And so the idea is to make that possible, as you said you've to be able to find the data when you need it. That's the data search and discovery. You've to be able to interpret that data correctly and draw valid conclusions from it. And that's a data literacy, excuse me. And both of those are contingent upon having data governance in place. So that data is well-defined and has high data quality, as well as other aspects, so that it is possible to find it and understand it properly. >> Right. And what are the things too that I think is really important that we call that, and again, we're going to dive into the details, is your perceived execution versus the reported execution by the people that are actually providing data. And I think you've found and you've highlighted on specific slides that you know, there's not necessarily a match there. And sometimes that you know, what you perceive is happening, isn't necessarily what's happening when you go down and query the people in the field. So really important to come up with a number. And I think a, I think you said this is going to be an ongoing thing over a period of time. So you kind of start to see longitudinal changes in these organizations. >> Absolutely. And we're very excited to see those, those trends over time. But even at the outset is this you know, very striking effect emerges which is, as you said, if we ask one of these you know, 300 data leaders, you know, all around the world actually, you know, if we ask, how is the data culture at your company overall, and this is very broad general top down way and have them graded on the sort of SaaS scale. You know, we get results where there's a large gap between kind of that level of maturity and what emerges in a bottom up methodology excuse me, in which you ask about, you know governance and literacy and, and such kind of by department and in a more bottom up way. And so we do see that that, you know, it can be helpful, even for data people to have a, a more granular metric and framework for quantifying their progress. >> Right? Let's jump into some of the results. It's, it's a fascinating, they're kind of all over the map, but there's some definite trends. One of the trends you talked about is that there's a lot of questions on the quality of the data. But that's a real inhibitor to people. Whether that suspicion is because it's not good data. And I don't know, this question for you, is, is, do they think it's not relevant to the decision that's being made? Is it an incomplete data set or the wrong data set? It seems to be that keeps coming up over and over about, decision-makers not necessarily having confidence in the data. What, can you share a little bit more color around that? >> Yeah, it's quite interesting actually. So what we find is that 90%. So 90 people, 10 executives (indistinct) to question the data sometimes often or always. But the part that's maybe disappointing or concerning is the two thirds of executives are believed to ignore the data and make a decision kind of pushing the data aside which is really quite striking when you think about it, why have all this data, if more often than not you're sort of disregarding it to make your final answer. And so you're absolutely correct when we dug into why, what are the reasons behind pushing it aside. Data quality was number one. And I think it is a question of, Oh, is the data inaccurate? Is it out of date, these sort of concerns sort of we, we hear from customers and prospects. But as we dig in deeper in the survey results, excuse me, we, we see some other reasons behind that. One is a lack of collaboration between the data analytics folks and the business folks. And so there's a question of, I don't know exactly where this data came from or to your point kind of how it was produced. What was the methodology? How was it sourced? And maybe because of that disconnect is a lack of trust. So trust really is the ultimate I think, failure to having data culture really take root. >> Right? And it's trust in this trust, as you said, not only in the data per se, the source of the data, the quality of the data, the relevance of the data but also the people who are providing you with the data. And obviously you get, you get some data sets. Sometimes you didn't get other data sets. So, that's really I'm a little bit disconcerting. The other thing I thought was kind of interesting is, it seems to be consistent that the, the primary reason that people are using big data projects is around operations and operations efficiency, a little bit about compliance, but, you know, it's interesting we had you on at the MIT CDOIQ, Chief Data Information Officer quality symposium, and you talked about the goodness of people moving from kind of a defensive posture to an offensive posture, you know using data in terms of product development and innovation. And, and what comes across in this survey is that's kind of down the list behind you know, kind of operational efficiency. We're seeing a little bit of governance and regulation but the, the quest for data as a tool for innovation, didn't really shine through in this report. >> Well, you know, it's very interesting. It depends whether you look at the aggregate level or you break things down a little bit more. So one thing we did after we got that zero to 12 scale on the data culture index or DCI, is it actually, we were able to break it down into thirds. And among the sort of bottom third, it has the least well-established data culture by this yardstick. We've found that governance and regulatory compliance, was the number one application of data. But among the top third of respondents, we actually found the opposite where things like providing a great customer experience, doing product innovation, those sort of things actually came to the fore and governance fell behind. So I think there is this curve where, It's table stakes to get the sort of defense side of data figured out. And then you can move on to offense in using data to make your organization meet its meet its other goals. >> Right. Right. And then I wanted to get your take on kind of the democratization of data, right? This is a, this is a trend that's been going on, and really, I think you said before you know, your guys' whole mission is to empower curious and rational world to give people the ability to ask the right questions have the right data and get the right answer. So, you know, we've seen democratization in terms of the access to the data, the access to the tools, the ability to do something with the data and the tool, and then the actual authority to execute business decision based on that. The results on that seem a little bit split here because a lot of the problems seem to be focused on leadership, not necessarily taking a data based decision move, but on the good hand a lot of people trying to break down data silos and make data more accessible for a larger group of people. So that more people in the organization are making data based decisions. This seems kind of like this little bit of a bifurcation between the C suite and everybody else trying to get their job done. >> Absolutely. There's always this question of you know, sort of the, that organizational wide initiative and then what's happening on the ground. One thing we saw that was very heartening and aligns with our customers index success, is a real emphasis being placed on having data governance and data context and data literacy factors sort of be embedded at the point of use. To not expecting people, to just like take a course and look things up and kind of end up with their workflow to be able to use data quickly and accurately and, and interpret it in varied ways. So that was really exciting to see as, as, as a initiative. It sort of bridges that gap along with initiatives to have more collaboration and integration between the data people and the business people. because really you know, they exist to serve one another. But in terms of the disconnect between the C suite and other parts of the org, there was a really interesting inverse correlation. Well, or maybe it's not interesting how you look at it, but basically, you know, when we talk to C level executives and ask, you know, does the C suite ignore data? Do they question data et cetera, those numbers came in lower than when we talked to, you know, senior director about the C suite right? It's sort of the farther you get, and there's a difference there, you know, from my perspective, I almost wonder whether that distance is actually is more objective viewpoint. And when you're in that role, it's hard to even see your cognitive biases and your tendency to ignore a data when it doesn't suit you. >> Right. Right. So there's, there's some other interesting things here. So one of them is, you know, kind of predictors, right? One of the whole reasons to do studies and collect data so that we can have some predictive ability. And, and it comes out here that the reporting structure is a strong predictor of a company's data tier structure. So, you know, there's the whole rise of the chief data officers and the chief analytics officer and the chief data and analytics officer and lots of conversations about those roles and what exactly are those roles and who do they report to. Your study finds a pretty compelling leading indicator that if that role is reporting to either the CEO or the executive board, which is often a one in the same person, that that's actually a terrific indicator of success in moving to a more data centric culture. >> That's absolutely correct. So we found that that top third of organizations on the data culture index were much more likely to have a chief data executive, a CDO, CAO or CDAO. In fact, they're more likely to have folks with the analytics in their title because in some organizations, data is thought to mean sort of raw data, infrastructural defense and analytics is sort of where it gets you know, infused into business processes and value. But certainly that top third is much more likely to have the chief data executive reporting into the executive board or CEO when the highest ranking data executive is under the CIO or some other part of the organization, those orgs tend to score a far lower on the DCI. >> Right. Right. So it's interesting, you know you're a really interesting guy even doing this for a while. You were at Siri before you were at Alation. So you have a really good feel for kind of what data can do and can't do and natural human or natural language processing and, and, and human voice interaction with these devices, a really interesting case study, and they can do a really good job within a small defined data set and instruction set, but they don't do necessarily so well once you kind of get outside how, how they're trained. And you've talked a lot about how metaphor shaped the way that we think and I know you and Dave talked about data oil and data lakes I don't want to necessarily go down that whole path but I do think it's important. And what came out of the study and the way people think about data. You know, there's a lot of conversation. How do you value data? Is data, you know it used to just be an expense that we had to buy servers to store the stuff we weren't sure what we ever did with it. So I wonder if there's any, you know, kind of top level metaphors level, kind of a thought or process or framing in the companies that you study that came out. maybe not necessarily in the top line data, but maybe in some of the notes that help define why some people, you know are being successful at making this transition and putting, you know kind of data out front of their decision processing versus data, either behind as a supporting thing or maybe data, I just don't have time with it or I don't trust it, or God knows where you got that, and this is not the data that I wanted. You know, was there any, you know, kind of tangental or anecdotal stuff that came out of this study that's more reflective of, of the softer parts of a data culture versus the harder parts in terms of titles and roles and, and, and job responsibilities. >> Yeah. It's a really interesting place to explore. I do think there's a, I don't want to make this overly simplistic group binary, but at the end of the day you know, like anything else within an organization, you can view data as a liability to say, okay, we have for example, you know, customer's names and phone numbers and passwords, and we just need to prevent an adverse event in which there's a leak or some sort of InfoSec problem that could cause, you know, bad press and fines and other negative consequences. And I think the issue there is if data's a liability, the most you know, the best case is that it's worth zero as opposed to some huge negative on your company's balance sheet. And, and I think, you know, intuitively, if you really want to prevent data misuse and data problems, one fail safe, but I think ultimately in its own way risky way to do that was just not collect any data, right. And not store it. So I think that the transition is to say, look data must be protected and taken care of that's step zero. But you know, it's really just the beginning and data is this asset that can be used to inform the huge company level strategic decisions that are made in annual planning at the board level, down to the millions of little decisions every day in the work of people in customer support and in sales and in product management and in, you know, various roles that just across industries. And I think once you have that, that shift, you know the upside is potentially, you know, unbounded. >> Right. And, and it just changes the way, the way you think. And suddenly instead of saying, Oh, data needs to be kind of hidden away, it's more like, Oh, people need to be trained on data use and empowered with data. And it's all about not if it's used or if it's misused but really how it's used and why it's used, what it's being used for to make a real impact. >> Right. Right. And it's funny when I just remember it being back in business school one of the great things that help teach is to think in terms of data, right. And you always have the infamous center consulting interview question, How many manhole covers are in Manhattan. Right. So, you know, to, to, to start to think about that problem from a data centric, point of view really gives you a leg up and, and even, you know where to start and how to attack those types of problems. And I thought it was interesting you know, talking about challenges for people to have a more data centric, point of view. It's interesting. The reports says, basically everybody said there's all kinds of challenges around data quality and compliance, and they had democratization. But the bottom companies, the bottom companies said that the biggest challenge was lack of buy in from company leadership. So I guess the good news bad news is that there's a real opportunity to make a significant change and get your company from the bottom third to a middle third or a top third, simply by taking a change in attitude about putting data in a much more central role in your decision making process. 'Cause all the other stuff's kind of operational, execution challenges that we all have, not enough people, blah, blah, blah. But in terms of attitude of leadership and prioritization, that's something that's very easy to change if you so choose. And really seems to be the key to unlock this real journey as opposed to the minutiae of a lot of the little details that that are a challenge for everybody. >> Absolutely. In your changing attitudes might be the easiest thing or the hardest thing depending on (indistinct). But I think you're absolutely right. The first step, which, which which could, maybe it should be easy, is admitting that you have a problem or maybe to put it more positively, realizing you have an opportunity. >> I love that. And then just again, looking at the top tier companies, the other thing that I thought was pretty interesting in this study is, I'm looking at it here, is getting champions in each of the operational segments. So rather than, I mean, a chief data officer is important and you know, somebody kind of at the high level to shepherd it in the executive suite, as we just discussed, but within each of the individual tasks and functions and roles, whether that's operations or customer service or product development or operational efficiency, you need some type of champion, some type of person, you know, banging the gavel, collecting the data, smoothing out the complexities, helping people get their thing together. And again, another way to really elevate your position on the score. >> Absolutely. And I think this idea of again, bridging between, you know, if data is centralized you have a chance to try to really get excellent practices within the data org. But even it becomes even more essential to have those ambassadors, people who are in the business and understand all the business context who can sort of make the data relevant, identify the key areas where data can really help, maybe demystify data and pick the right metaphors and the right examples to make it real for the people in their function. >> Right. Right. So Aaron has a lot of great stuff. People can go to the website at alation.com. I'm sure you'll have a link to this, a very prominently displayed, but, and they should and they should check it out and really think about it and think about how it applies to their own situation, their own department, company et cetera. I just wanted to give you the last word before we before we sign off, you know, kind of what was the most you know, kind of positive affirmation or not the most but one or two of the most outcome affirming outcomes of this exercise. And what were one or two of the things that were a little concerning or, you know, kind of surprises on the downside that, that came out of this research? >> Yeah. So I think one thing that was maybe surprising or concerning the biggest one is sort of where we started with that disconnect between, you know, what people would, say as an off the cuff overall assessment and the disconnect between that and what emerges when we go department by department and (indistinct) to be pillars of data culture from such a discovery to data literacy, to data governance. I think that disconnect, you know, should give one pause. I think certainly it should make one think, Hmm. Maybe I shouldn't look from 10,000 feet, but actually be a little more systematic. And considering the framework I use to assess data culture that is the most important thing to my organization. I think though, there's this quote that you move what you measure, just having this hopefully simple but not simplistic yardstick to measure data culture and the data culture index should help people be a little bit more realistic in their quantification and they track their progress, you know, quarter over quarter. So I think that's very promising. I think another thing is that, you know sometimes we ask, how long have you had this initiative? How much progress have you made? And it can sometimes seem like pushing a boulder uphill. Obviously the COVID pandemic and the economic impacts of that has been really tragic and really hard. You know, a tiny silver lining in that is the survey results showed that organizations have really observed a shift in how much they're using data because sometimes things are changing but it's like a frog in boiling water. You don't realize it. And so you just assume that the future is going to look like the recent past and you don't look at the data or you ignore the data or you miss parts of the data. And a lot of organizations said, you know COVID was this really troubling wake up call, but they could even after this crisis is over, producing enduring change which people were consulting data more and making decisions in a more data driven way. >> Yeah, certainly an accelerant that, that is for sure whether you wanted it, didn't want it, thought you had it at the time, didn't have time. You know COVID is definitely digital transformation accelerant and data is certainly the thing that powers that. Well again, it's the Alation State of Data Culture Report available, go check it at alation.com. Aaron always great to catch up and again, thank you for, for doing the work and supporting this research. And I think it's really important stuff. And it's going to be interesting to see how it changes over time. 'Cause that's really when these types of reports really start to add value. >> Thanks for having me, Jeff and I really look forward to discussing some of those trends as the research is completed. >> All right. Thanks a lot, Aaron, take care. Alright. He's Aaron and I'm Jeff. You're watching theCUBE, Palo Alto. Thanks for watching. We'll see you next time. (upbeat music)