(upbeat music) >> Welcome back to The Cubes coverage of WIDS 2023 the eighth Annual Women in Data Science Conference which is held at Stanford University. I'm your host, Lisa Martin. I'm really excited to be having some great co-hosts today. I've got Hannah Freytag with me, who is a data journalism master student at Stanford. We have yet another inspiring woman in technology to bring to you today. Kelly Hoang joins us, data scientist at Gilead. It's so great to have you, Kelly. >> Hi, thank you for having me today. I'm super excited to be here and share my journey with you guys. >> Let's talk about that journey. You recently got your PhD in information sciences, congratulations. >> Thank you. Yes, I just graduated, I completed my PhD in information sciences from University of Illinois Urbana-Champaign. And right now I moved to Bay Area and started my career as a data scientist at Gilead. >> And you're in better climate. Well, we do get snow here. >> Kelly: That's true. >> We proved that the last... And data science can show us all the climate change that's going on here. >> That's true. That's the topic of the data fund this year, right? To understand the changes in the climate. >> Yeah. Talk a little bit about your background. You were mentioning before we went live that you come from a whole family of STEM students. So you had that kind of in your DNA. >> Well, I consider myself maybe I was a lucky case. I did grew up in a family in the STEM environment. My dad actually was a professor in computer science. So I remember when I was at a very young age, I already see like datas, all of these computer science concepts. So grew up to be a data scientist is always something like in my mind. >> You aspired to be. >> Yes. >> I love that. >> So I consider myself in a lucky place in that way. But also, like during this journey to become a data scientist you need to navigate yourself too, right? Like you have this roots, like this foundation but then you still need to kind of like figure out yourself what is it? Is it really the career that you want to pursue? But I'm happy that I'm end up here today and where I am right now. >> Oh, we're happy to have you. >> Yeah. So you' re with Gilead now after you're completing your PhD. And were you always interested in the intersection of data science and health, or is that something you explored throughout your studies? >> Oh, that's an excellent question. So I did have background in computer science but I only really get into biomedical domain when I did my PhD at school. So my research during my PhD was natural language processing, NLP and machine learning and their applications in biomedical domains. And then when I graduated, I got my first job in Gilead Science. Is super, super close and super relevant to what my research at school. And at Gilead, I am working in the advanced analytics department, and our focus is to bring artificial intelligence and machine learning into supporting clinical decision making. And really the ultimate goal is how to use AI to accelerate the precision medicine. So yes, it's something very like... I'm very lucky to get the first job that which is very close to my research at school. >> That's outstanding. You know, when we talk about AI, we can't not talk about ethics, bias. >> Kelly: Right. >> We know there's (crosstalk) Yes. >> Kelly: In healthcare. >> Exactly. Exactly. Equities in healthcare, equities in so many things. Talk a little bit about what excites you about AI, what you're doing at Gilead to really influence... I mean this, we're talking about something that's influencing life and death situations. >> Kelly: Right. >> How are you using AI in a way that is really maximizing the opportunities that AI can bring and maximizing the value in the data, but helping to dial down some of the challenges that come with AI? >> Yep. So as you may know already with the digitalization of medical records, this is nowaday, we have a tremendous opportunities to fulfill the dream of precision medicine. And what I mean by precision medicines, means now the treatments for people can be really tailored to individual patients depending on their own like characteristic or demographic or whatever. And nature language processing and machine learning, and AI in general really play a key role in that innovation, right? Because like there's a vast amount of information of patients and patient journeys or patient treatment is conducted and recorded in text. So that's why our group was established. Actually our department, advanced analytic department in Gilead is pretty new. We established our department last year. >> Oh wow. >> But really our mission is to bring AI into this field because we see the opportunity now. We have a vast amount of data about patient about their treatments, how we can mine these data how we can understand and tailor the treatment to individuals. And give everyone better care. >> I love that you brought up precision medicine. You know, I always think, if I kind of abstract everything, technology, data, connectivity, we have this expectation in our consumer lives. We can get anything we want. Not only can we get anything we want but we expect whoever we're engaging with, whether it's Amazon or Uber or Netflix to know enough about me to get me that precise next step. I don't think about precision medicine but you bring up such a great point. We expect these tailored experiences in our personal lives. Why not expect that in medicine as well? And have a tailored treatment plan based on whatever you have, based on data, your genetics, and being able to use NLP, machine learning and AI to drive that is really exciting. >> Yeah. You recap it very well, but then you also bring up a good point about the challenges to bring AI into this field right? Definitely this is an emerging field, but also very challenging because we talk about human health. We are doing the work that have direct impact to human health. So everything need to be... Whatever model, machine learning model that you are building, developing you need to be precise. It need to be evaluated properly before like using as a product, apply into the real practice. So it's not like recommendation systems for shopping or anything like that. We're talking about our actual health. So yes, it's challenging that way. >> Yeah. With that, you already answered one of the next questions I had because like medical data and health data is very sensitive. And how you at Gilead, you know, try to protect this data to protect like the human beings, you know, who are the data in the end. >> The security aspect is critical. You bring up a great point about sensitive data. We think of healthcare as sensitive data. Or PII if you're doing a bank transaction. We have to be so careful with that. Where is security, data security, in your everyday work practices within data science? Is it... I imagine it's a fundamental piece. >> Yes, for sure. We at Gilead, for sure, in data science organization we have like intensive trainings for employees about data privacy and security, how you use the data. But then also at the same time, when we work directly with dataset, it's not that we have like direct information about patient at like very granular level. Everything is need to be kind of like anonymized at some points to protect patient privacy. So we do have rules, policies to follow to put that in place in our organization. >> Very much needed. So some of the conversations we heard, were you able to hear the keynote this morning? >> Yes. I did. I attended. Like I listened to all of them. >> Isn't it fantastic? >> Yes, yes. Especially hearing these women from different backgrounds, at different level of their professional life, sharing their journeys. It's really inspiring. >> And Hannah, and I've been talking about, a lot of those journeys look like this. >> I know >> You just kind of go... It's very... Yours is linear, but you're kind of the exception. >> Yeah, this is why I consider my case as I was lucky to grow up in STEM environment. But then again, back to my point at the beginning, sometimes you need to navigate yourself too. Like I did mention about, I did my pa... Sorry, my bachelor degree in Vietnam, in STEM and in computer science. And that time, there's only five girls in a class of 100 students. So I was not the smartest person in the room. And I kept my minority in that areas, right? So at some point I asked myself like, "Huh, I don't know. Is this really my careers." It seems that others, like male people or students, they did better than me. But then you kind of like, I always have this passion of datas. So you just like navigate yourself, keep pushing yourself over those journey. And like being where I am right now. >> And look what you've accomplished. >> Thank you. >> Yeah. That's very inspiring. And yeah, you mentioned how you were in the classroom and you were only one of the few women in the room. And what inspired or motivated you to keep going, even though sometimes you were at these points where you're like, "Okay, is this the right thing?" "Is this the right thing for me?" What motivated you to keep going? >> Well, I think personally for me, as a data scientist or for woman working in data science in general, I always try to find a good story from data. Like it's not, when you have a data set, well it's important for you to come up with methodologies, what are you going to do with the dataset? But I think it's even more important to kind of like getting the context of the dataset. Like think about it like what is the story behind this dataset? What is the thing that you can get out of it and what is the meaning behind? How can we use it to help use it in a useful way. To have in some certain use case. So I always have that like curiosity and encouragement in myself. Like every time someone handed me a data set, I always think about that. So it's helped me to like build up this kind of like passion for me. And then yeah. And then become a data scientist. >> So you had that internal drive. I think it's in your DNA as well. When you were one of five. You were 5% women in your computer science undergrad in Vietnam. Yet as Hannah was asking you, you found a lot of motivation from within. You embrace that, which is so key. When we look at some of the statistics, speaking of data, of women in technical roles. We've seen it hover around 25% the last few years, probably five to 10. I was reading some data from anitab.org over the weekend, and it shows that it's now, in 2022, the number of women in technical roles rose slightly, but it rose, 27.6%. So we're seeing the needle move slowly. But one of the challenges that still remains is attrition. Women who are leaving the role. You've got your PhD. You have a 10 month old, you've got more than one child. What would you advise to women who might be at that crossroads of not knowing should I continue my career in climbing the ladder, or do I just go be with my family or do something else? What's your advice to them in terms of staying the path? >> I think it's really down to that you need to follow your passion. Like in any kind of job, not only like in data science right? If you want to be a baker, or you want to be a chef, or you want to be a software engineer. It's really like you need to ask yourself is it something that you're really passionate about? Because if you really passionate about something, regardless how difficult it is, like regardless like you have so many kids to take care of, you have the whole family to take care of. You have this and that. You still can find your time to spend on it. So it's really like let yourself drive your own passion. Drive the way where you leading to. I guess that's my advice. >> Kind of like following your own North Star, right? Is what you're suggesting. >> Yeah. >> What role have mentors played in your career path, to where you are now? Have you had mentors on the way or people who inspired you? >> Well, I did. I certainly met quite a lot of women who inspired me during my journey. But right now, at this moment, one person, particular person that I just popped into my mind is my current manager. She's also data scientist. She's originally from Caribbean and then came to the US, did her PhDs too, and now led a group, all women. So believe it or not, I am in a group of all women working in data science. So she's really like someone inspire me a lot, like someone I look up to in this career. >> I love that. You went from being one of five females in a class of 100, to now having a PhD in information sciences, and being on an all female data science team. That's pretty cool. >> It's great. Yeah, it's great. And then you see how fascinating that, how things shift right? And now today we are here in a conference that all are women in data science. >> Yeah. >> It's extraordinary. >> So this year we're fortunate to have WIDS coincide this year with the actual International Women's Day, March 8th which is so exciting. Which is always around this time of year, but it's great to have it on the day. The theme of this International Women's Day this year is embrace equity. When you think of that theme, and your career path, and what you're doing now, and who inspires you, how can companies like Gilead benefit from embracing equity? What are your thoughts on that as a theme? >> So I feel like I'm very lucky to get my first job at Gilead. Not only because the work that we are doing here very close to my research at school, but also because of the working environment at Gilead. Inclusion actually is one of the five core values of Gilead. >> Nice. >> So by that, we means we try to create and creating a working environment that all of the differences are valued. Like regardless your background, your gender. So at Gilead, we have women at Gilead which is a global network of female employees, that help us to strengthen our inclusion culture, and also to influence our voices into the company cultural company policy and practice. So yeah, I'm very lucky to work in the environment nowadays. >> It's impressive to not only hear that you're on an all female data science team, but what Gilead is doing and the actions they're taking. It's one thing, we've talked about this Hannah, for companies, and regardless of industry, to say we're going to have 50% women in our workforce by 2030, 2035, 2040. It's a whole other ballgame for companies like Gilead to actually be putting pen to paper. To actually be creating a strategy that they're executing on. That's awesome. And it must feel good to be a part of a company who's really adapting its culture to be more inclusive, because there's so much value that comes from inclusivity, thought diversity, that ultimately will help Gilead produce better products and services. >> Yeah. Yes. Yeah. Actually this here is the first year Gilead is a sponsor of the WIDS Conference. And we are so excited to establish this relationship, and looking forward to like having more collaboration with WIDS in the future. >> Excellent. Kelly we've had such a pleasure having you on the program. Thank you for sharing your linear path. You are definitely a unicorn. We appreciate your insights and your advice to those who might be navigating similar situations. Thank you for being on theCUBE today. >> Thank you so much for having me. >> Oh, it was our pleasure. For our guests, and Hannah Freytag this is Lisa Martin from theCUBE. Coming to you from WIDS 2023, the eighth annual conference. Stick around. Our final guest joins us in just a minute.

>>Good afternoon everyone, and thank you so much for joining us. My name is Savannah Peterson, joined by my co-host Paul for the afternoon. Very excited. Oh, Savannah. Hello. I'm, I'm pumped for this. This is our first bit together. Exactly. >>It's gonna be fun. Yes. We have a great guest to kick off with. >>We absolutely do. We're at Supercomputing 2022 today, and very excited to talk to our next guest. We're gonna be talking about data at scale and data that really matters to us joining us. Kelly Gayer, thank you so much for being here and you are with tech. Tell everyone what TAC is. >>Tech is the Texas Advanced Computing Center at the University of Texas at Austin. And thank you so much for having me here. >>It is wonderful to have you. Your smile's contagious. And one of the themes that's come up a lot with all of our guests, and we just talked about it, is how good it is to be back in person, how good it is to be around our hardware, community tech. You did some very interesting research during the pandemic. Can you tell us about that? >>I can. I did. So when we realized sort of mid-March, we realized that, that this was really not normal times and the pandemic was statement. Yes. That pandemic was really gonna touch everyone. I think a lot of us at the center and me personally, we dropped everything to plug in and that's what we do. So UT's tagline is what starts here changes the world and tax tagline is powering discoveries that change the world. So we're all about impact, but I plugged in with the research group there at UT Austin, Dr. Lauren Myers, who's an epidemiologist, and just we figured out how to plug in and compute so that we could predict the spread of, of Covid 19. >>And you did that through the use of mobility data, cell phone signals. Tell us more about what exactly you were choreographing. >>Yeah, so that was really interesting. Safe graph during the pandemic made their mobility data. Typically it was used for marketing purposes to know who was going into Walmart. The offenses >>For advertising. >>Absolutely, yeah. They made all of their mobility data available for free to people who were doing research and plugging in trying to understand Covid. 19, I picked that data up and we used it as a proxy for human behavior. So we knew we had some idea, we got weekly mobility updates, but it was really mobility all day long, you know, anonymized. I didn't know who they were by cell phones across the US by census block group or zip code if we wanted to look at it that way. And we could see how people were moving around. We knew what their neighbor, their home neighborhoods were. We knew how they were traveling or not traveling. We knew where people were congregating, and we could get some idea of, of how people were behaving. Were they really, were they really locking down or were they moving in their neighborhoods or were they going outside of their neighborhoods? >>What a, what a fascinating window into our pandemic lives. So now that you were able to do this for this pandemic, as we look forward, what have you learned? How quickly could we forecast? What's the prognosis? >>Yeah, so we, we learned a tremendous amount. I think during the pandemic we were reacting, we were really trying. It was a, it was an interesting time as a scientist, we were reacting to things almost as if the earth was moving underneath us every single day. So it was something new every day. And I've told people since I've, I haven't, I haven't worked that hard since I was a graduate student. So it was really daylight to dark 24 7 for a long period of time because it was so important. And we knew, we, we knew we were, we were being a part of history and affecting something that was gonna make a difference for a really long time. And, and I think what we've learned is that indeed there is a lot of data being collected that we can use for good. We can really understand if we get organized and we get set up, we can use this data as a means of perhaps predicting our next pandemic or our next outbreak of whatever. It is almost like using it as a canary in the coal mine. There's a lot in human behavior we can use, given >>All the politicization of, of this last pandemic, knowing what we know now, making us better prepared in theory for the next one. How confident are you that at least in the US we will respond proactively and, and effectively when the next one comes around? >>Yeah, I mean, that's a, that's a great question and, and I certainly understand why you ask. I think in my experience as a scientist, certainly at tech, the more transparent you are with what you do and the more you explain things. Again, during the pandemic, things were shifting so rapidly we were reacting and doing the best that we could. And I think one thing we did right was we admitted where we felt uncertain. And that's important. You have to really be transparent to the general public. I, I don't know how well people are gonna react. I think if we have time to prepare, to communicate and always be really transparent about it. I think those are three factors that go into really increasing people's trust. >>I think you nailed it. And, and especially during times of chaos and disaster, you don't know who to trust or what to believe. And it sounds like, you know, providing a transparent source of truth is, is so critical. How do you protect the sensitive data that you're working with? I know it's a top priority for you and the team. >>It is, it is. And we, we've adopted the medical mantra, do no harm. So we have, we feel a great responsibility there. There's, you know, two things that you have to really keep in mind when you've got sensitive data. One is the physical protection of it. And so that's, that's governed by rule, federal rules, hipaa, ferpa, whatever, whatever kind of data that you have. So we certainly focus on the physical protection of it, but there's also sort of the ethical protection of it. What, what is the quote? There's lies, damn lies and statistics. >>Yes. Twain. >>Yeah. So you, you really have to be responsible with what you're doing with the data, how you're portraying the results. And again, I think it comes back to transparency is is basically if people are gonna reproduce what I did, I have to be really transparent with what I did. >>I, yeah, I think that's super important. And one of the themes with, with HPC that we've been talking about a lot too is, you know, do people trust ai? Do they trust all the data that's going into these systems? And I love that you just talked about the storytelling aspect of that, because there is a duty, it's not, you can cut data kind of however you want. I mean, I come from marketing background and we can massage it to, to do whatever we want. So in addition to being the deputy director at Tech, you are also the DEI officer. And diversity I know is important to you probably both as an individual, but also in the work that you're doing. Talk to us about that. >>Yeah, I mean, I, I very passionate about diversity, equity and inclusion in a sense of belongingness. I think that's one of the key aspects of it. Core >>Of community too. >>I got a computer science degree back in the eighties. I was akin to a unicorn in a, in an engineering computer science department. And, but I was really lucky in a couple of respects. I had a, I had a father that was into science that told me I could do anything I, I wanted to set my mind to do. So that was my whole life, was really having that support system. >>He was cheers to dad. >>Yeah. Oh yeah. And my mom as well, actually, you know, they were educators. I grew up, you know, in that respect, very, very privileged, but it was still really hard to make it. And I couldn't have told you back in that time why I made it and, and others didn't, why they dropped out. But I made it a mission probably back, gosh, maybe 10, 15 years ago, that I was really gonna do all that I could to change the needle. And it turns out that there are a number of things that you can do grassroots. There are certainly best practices. There are rules and there are things that you really, you know, best practices to follow to make people feel more included in an organization, to feel like they belong it, shared mission. But there are also clever things that you can do with programming to really engage students, to meet people and students where they are interested and where they are engaged. And I think that's what, that's what we've done over, you know, the course of our programming over the course of about maybe since 2016. We have built a lot of programming ATAC that really focuses on that as well, because I'm determined the needle is gonna change before it's all said and done. It just really has to. >>So what, what progress have you made and what goals have you set in this area? >>Yeah, that, that's a great question. So, you know, at first I was a little bit reluctant to set concrete goals because I really didn't know what we could accomplish. I really wasn't sure what grassroots efforts was gonna be able to, you're >>So honest, you can tell how transparent you are with the data as well. That's >>Great. Yeah, I mean, if I really, most of the successful work that I've done is both a scientist and in the education and outreach space is really trust relationships. If I break that trust, I'm done. I'm no longer effective. So yeah, I am really transparent about it. But, but what we did was, you know, the first thing we did was we counted, you know, to the extent that we could, what does the current picture look like? Let's be honest about it. Start where we are. Yep. It was not a pretty picture. I mean, we knew that anecdotally it was not gonna be a great picture, but we put it out there and we leaned into it. We said, this is what it is. We, you know, I hesitated to say we're gonna look 10% better next year because I'm, I'm gonna be honest, I don't always know we're gonna do our best. >>The things that I think we did really well was that we stopped to take time to talk and find out what people were interested in. It's almost like being present and listening. My grandmother had a saying, you have two errors in one mouth for a reason, just respect the ratio. Oh, I love that. Yeah. And I think it's just been building relationships, building trust, really focusing on making a difference, making it a priority. And I think now what we're doing is we've been successful in pockets of people in the center and we are, we are getting everybody on board. There's, there's something everyone can do, >>But the problem you're addressing doesn't begin in college. It begins much, much, that's right. And there's been a lot of talk about STEM education, particularly for girls, how they're pushed out of the system early on. Also for, for people of color. Do you see meaningful progress being made there now after years of, of lip service? >>I do. I do. But it is, again, grassroots. We do have a, a, a researcher who was a former teacher at the center, Carol Fletcher, who is doing research and for CS for all we know that the workforce, so if you work from the current workforce, her projected workforce backwards, we know that digital skills of some kind are gonna be needed. We also know we have a, a, a shortage. There's debate on how large that shortage is, but about roughly about 1 million unmet jobs was projected in 2020. It hasn't gotten a lot better. We can work that problem backwards. So what we do there is a little, like a scatter shot approach. We know that people come in all forms, all shapes, all sizes. They get interested for all different kinds of reasons. We expanded our set of pathways so that we can get them where they can get on to the path all the way back K through 12, that's Carol's work. Rosie Gomez at the center is doing sort of the undergraduate space. We've got Don Hunter that does it, middle school, high school space. So we are working all parts of the problem. I am pretty passionate about what we consider opportunity youth people who never had the opportunity to go to college. Is there a way that we can skill them and get, get them engaged in some aspect and perhaps get them into this workforce. >>I love that you're starting off so young. So give us an example of one of those programs. What are you talking to kindergartners about when it comes to CS education? >>You know, I mean, gaming. Yes. Right. It's what everybody can wrap their head around. So most kids have had some sort of gaming device. You talk in the context, in the context of something they understand. I'm not gonna talk to them about high performance computing. It, it would go right over their heads. And I think, yeah, you know, I, I'll go back to something that you said Paul, about, you know, girls were pushed out. I don't know that girls are being pushed out. I think girls aren't interested and things that are being presented and I think they, I >>Think you're generous. >>Yeah. I mean, I was a young girl and I don't know why I stayed. Well, I do know why I stayed with it because I had a father that saw something in me and I had people at critical points in my life that saw something in me that I didn't see. But I think if we ch, if we change the way we teach it, maybe in your words they don't get pushed out or they, or they won't lose interest. There's, there's some sort of computing in everything we do. Well, >>Absolutely. There's also the bro culture, which begins at a very early >>Age. Yeah, that's a different problem. Yeah. That's just having boys in the classroom. Absolutely. You got >>It. That's a whole nother case. >>That's a whole other thing. >>Last question for you, when we are sitting here, well actually I've got, it's two parter, let's put it that way. Is there a tool or something you wish you could flick a magic wand that would make your job easier? Where you, you know, is there, can you identify the, the linchpin in the DEI challenge? Or is it all still prototyping and iterating to figure out the best fit? >>Yeah, that is a, that's a wonderful question. I can tell you what I get frustrated with is that, that >>Counts >>Is that I, I feel like a lot of people don't fully understand the level of effort and engagement it takes to do something meaningful. The >>Commitment to a program, >>The commitment to a program. Totally agree. It's, there is no one and done. No. And in fact, if I do that, I will lose them forever. They'll be, they will, they will be lost in the space forever. Rather. The engagement is really sort of time intensive. It's relationship intensive, but there's a lot of follow up too. And the, the amount of funding that goes into this space really is not, it, it, it's not equal to the amount of time and effort that it really takes. And I think, you know, I think what you work in this space, you realize that what you gain is, is really more of, it's, it really feels good to make a difference in somebody's life, but it's really hard to do on a shoer budget. So if I could kind of wave a magic wand, yes, I would increase understanding. I would get people to understand that it's all of our responsibility. Yes, everybody is needed to make the difference and I would increase the funding that goes to the programs. >>I think that's awesome, Kelly, thank you for that. You all heard that. More funding for diversity, equity, and inclusion. Please Paul, thank you for a fantastic interview, Kelly. Hopefully everyone is now inspired to check out tac perhaps become a, a Longhorn, hook 'em and, and come deal with some of the most important data that we have going through our systems and predicting the future of our pandemics. Ladies and gentlemen, thank you for joining us online. We are here in Dallas, Texas at Supercomputing. My name is Savannah Peterson and I look forward to seeing you for our next segment.

>>Hey everyone. Welcome back to the Cube's coverage of snowflake summit. 22 live from Las Vegas. We're at Caesar's forum, Lisa Martin, with Dave ante. We've been having some great conversations over the last day and a half. This guy just came from main stage interviewing the CEO, Franks Lubin himself, who joins us after our next guest here, we're gonna be talking customers and successes with snowflake Rosemary Hua joins us the global head of retail at snowflake and Patrick Kelly, the VP of product management at their customer 84 51. Welcome to the program guys. >>Thank you. It's nice to be here. So >>Patrick, 84 51. Talk to us about the business, give the audience an overview of what you guys are doing. And then we'll talk about how you're working with snowflake. >>Yeah, absolutely. Thank you both for, uh, the opportunity to be here. So 84 51 is a retail data science insights and media company. And really what that means is that we, we partner with our, uh, parent company Kroger, as well as consumer packaged goods or brands and brokers and agencies, really to understand shoppers and create relevant, personalized, and valuable experiences for shoppers in source and grocery stores. >>That relevance is key. We all expect that these days, I think the last couple of years as everyone's patience has been wearing. Yeah, very thin. I'm not, I'm not convinced it's gonna come back either, but we expect that brands are gonna interact with us and offer us the next best offer. That's actually relevant and personalized to us. How does AB 4 51 achieve that? >>Yeah, it's a great question. And you're right. That expectation is only growing. Um, and it takes data analytics, data science and all of these capabilities in order to deliver it on that promise, uh, you know, big, a big part of the relationship that retailers and brands have with consumers is about a value exchange. And it's, again, it's about that expectation that brands and retailers need to be able to meet the ever-changing needs of consumers. Uh, whether that be introducing new brands or offering the right price points or promotions or ensuring you meet them where they are, whether it be online, which has obviously been catalyzed by, um, the pandemic over the last two years or in store. So a deep understanding of, of the customer, which is founded in data and the appropriate analytics and science, and then the collaboration back with the retailers and, and the brands so that you can bring that experience to life. Again, that could be a price point on the, on the shelf, um, or it could be a personalized email or, um, website interaction that delivers the right experience for the co for the consumer. So they can see that value and really build loyalty >>In the right time in real time. That's >>One of the most Marrit I'm in real time. That's right. One goes, Mary, I love the concept of the, the actual platform of the retail data cloud. Yes. It's so unique for a technology company. Snowflake's a technology company, you see services companies do it all the time, but yeah, but to actually transform what was considered a data warehouse in the cloud to a platform for data, I call it super cloud. Yeah. Tell us how this came about, um, how you were able to actually develop this and where you are in that journey. >>Yeah, absolutely. It's been a big focus on data sharing. We saw that that's how our customers are interacting with each other is using our data sharing functionality to really bring that ecosystem to life. So that's retailers sharing with their consumer products companies selling through those retailers. And then of course the data service companies that are kind of helping both sides and that data sharing functionality is the kind of under fabric for the data cloud, where we bring in partners. We bring in customers and we bring in tech solutions to the table. Um, and customers can use the data cloud, not only with the powered by partners that we have, but also the data marketplace, getting that data in real time and making some business value out of that data. So that's really the big focus of snowflake is investing in industry to realize the business value >>And talk about ecosystem and how important that is, where, where you leave off and the ecosystem picks up and how that's evolving. >>Absolutely. And I'm sure you can join in on this, but, um, definitely that collaboration between retailers and CPGs, right? I mean, retailers have that rich first party customer data. They see all those transactions, they see when people are shopping and then the brands really need that first party data to figure out what their, how their customers are interacting with their brand. And so that collaborative nature that makes up the ecosystem. And of course, you've got the tech partners in the middle that are kind of providing enrich data assets as well. You guys at 84 51 are a huge part of that ecosystem being, you know, one of the key retailers in, in the United States. Um, have you been seeing that as well with your brands? Yeah, >>Absolutely. I mean data and data science has always been core to the identity of 84 51. Um, and historically a lot of the interaction that we have with brands were through report web based applications, right. And it's a really great seamless way to, to deliver insights to non-technical users. But as the entire market has really started to invest in data and data science and technology and capabilities, you know, we, we launched a collaborative cloud last year and it was really an opportunity for us to reimagine what that experience would look like and to ensure that we are meeting the evolving needs of the industry. And as Rosemary pointed out, you know, data sharing is, is table stakes, right? It's a capability that you don't wanna have to think about. You wanna be thinking about the strategic initiatives, the science that you're gonna create in order to drive action and personalize experiences. So what we've found at 84 51 is really investing in our collaborative cloud, um, and working with leading technology providers like snowflake to make that seamless has been, you know, the, the, the UN unlock to ensure that data and data science can be a competitive advantage for our clients and partners, not just, you know, the retailer in 84 51 >>Is the collaborative cloud built on snowflake. >>Yeah. So the collaborative cloud is really about, um, ensuring that data sharing through snowflake is done seamlessly. So we've really, we've invited our clients and partners to build their own science on 84 51 S first party data asset through Kroger. And our, our data is represents 60 million households, half of the United States, 2 billion transactions annually, the robustness of that data asset. And it's it's it's analysis ready is so impactful to the investment that brands can make in their own data science efforts, because brands wanna invest in data science, not to do data work, not to do cleaning and Muning and, and merging and, and standardizing. They wanna do analysis. That's gonna impact the strategies and ultimately the shopper's lives. So again, we're able to leverage the capabilities of snowflake to ensure data sharing is not part of our day to day conversation. Data sharing is something we can take for granted so that we can talk about the shopper and our strategies. >>So this is why I call it super cloud. So Jerry Chen wrote an article of castles in the cloud. And in there he said, he called it sub clouds. And I'm like, no, it's, uh, by the way, great article. Jerry's brilliant. But so you got AWS, you built on top of AWS. That's right. You got the snowflake data called you're building on top of that. And I was sitting at the table and my kid goes, this is super, I'm like, ah, super clouds. So I didn't really even coin it, but, and then I realized somebody else had use it before, but that is different. It's new, it's around data. It's around vertical industries. Yes. Um, I, I get a lot of heat for that term, but I feel like this look around this industry, everybody's doing that that's that is digital transformation. That's don't you see that with your customers? >>Absolutely. I mean, there's a lot of different industry trends where you can't use your own historical first party data to figure out what customers are doing. I mean, with COVID customers are behaving totally differently than they used to. And you can't use your historical data to predict out of stocks or how the customer's gonna be interacting with your brand anymore. And you need that third party macroeconomic data. You need that third party COVID data or foot traffic data to enrich what your businesses are doing. And so, yes, it, it is a super cloud. And I think the big differentiator is that we are cloud agnostic, meaning that, like you said, you can take the technology for granted. You don't have to worry about where the other person has their tech stack. It's all the same experience on the snowflake super cloud as he put it. So, >>So Patrick, talk about the, the, the impact that you have been able to have during COVID. I mean, everybody had supply chain issues, but, you know, if you took, if you took away the machine learning and the data science that you are initiating, would life have been harder? Do you have data on that? You know, the, the, what if we didn't have this capability during the >>Challenges? No, it's, it's a fantastic question. And I'll actually build on the example that Rosemary, um, offered around COVID and better understanding COVID. So, um, in the past, you know, when we talk about data sharing data collaboration, it's basically wasn't possible, right? What's your tech stack, what's mine. How do we share data? I don't wanna send you my data without go releasing governance. It was a non-starter and, you know, through technology like snowflake, as we launched the collaborative cloud, we actually had a pilot client start right at the beginning of 2020. Um, we, we had, you know, speced out it onto use cases that really impactful for their, for their organization. But of course, what happened is, uh, a pandemic hit us and it became the biggest question, CEO executive team, all the way down is what is happening, what is happening in our stores? >>How are shoppers behaving and what, what that client of ours came to realize is while we, we actually, we have access to the E 4 51 collaborative cloud. We can see half of America's behavior last week down to the basket transaction UPC level. Let's get going. So again, the conversation wasn't about, you know, what data sources, how do we scramble? How do we get it together? What technologies, how do we collaborate? It was immediately focused on building the analysis to better understand that. And, and the outcomes that drove actually were all the way from manufacturing impact to marketing, to merchandising, because that brand was able to figure out, Hey, our top selling products, they're, they're not on the shelves. What are shoppers doing? Are they going to a, another brand? Are they not buying it all together? Are they going to a different size? Are they staying within our product portfolio? Are they going to a competitor? And those insights drove everything again from what do we need to manufacture more to, how do we need to communicate and incent our, our, our shoppers, our, our loyal shoppers also what's happening to our non loyals. Are they looking for an, you know, an alternative that a need that we can serve that level of, of shopper and customer understanding going all the way up to a strategic initiatives is something that is enabled through the Supercloud >><laugh>. How do you facilitate privacy as we're seeing this proliferation of privacy legislation? Yeah. I think there's now 22 states that have individual, and California's changing to CPR a at the beginning of yes, January 23. How do you balance that need that ability to share data? Yeah. Equitably fast, quickly, but also balance consumer privacy requirements. >>I mean, I could take a stab first. I mean, at snowflake, right, there is no better place to share your data that in a governed way than with snowflake data sharing, because then you can see and understand how the other side is using your data. Whereas in traditional methods, using an API or using an FTP server, you wouldn't be able to actually see how the other side is using your data. But in addition to that, we have the clean room where you can actually join on that underlying PII data without exposing it, because you can share functions securely on, on both sides. So I think there is no better place to do it than here at snowflake. Um, and because we deeply understand those policies, I think we are kind of keeping up with the times trying to get in front of things so that our data sharing capabilities stay up to date. When you have to expunge records, identify records with CCPA and, and GDPR and, and all the rest that are coming. Um, and so, so, I mean, I think especially with 84 50 ones, um, you know, collaborative cloud also building on top of the clean room, um, in, in further road in the further roadmap, I think, uh, you're gonna see some of that privacy compliant, data sharing, coming to play as well. You >>Know, what's interesting, Patrick is we were just in that session with the Frank Q and a, and he was very candid about when he was talking about, uh, Apache, uh, I'm sorry. Apache iceberg. Yeah. Yes. And he, he basically flat out said, look, you know, you gotta put it into the snowflake data cloud. It's, it's better there, but people might, you know, want to put it outside, not get locked in, et cetera. But what I'm, I'm listening to you saying it's so much easier for you today that could evolve something open source. And, and how do you think about that in terms of placing your bets? >>Yeah, it, it's a great question and really to go back to privacy, um, as a total topic, I mean, you're right. It's extremely relevant topic. It's, it's, you know, very ever changing right now at 84 51. Privacy is, is first it's the foundation. Um, it it's table stakes and that's from a policy that's from a governance, it's from a technology capability standpoint. And it's part of our, our culture because, um, it, it, because it has to be, uh, and, and so when we, when we think about, you know, the products that we're gonna build, how we want to implement, it's, it's a requirement that we leverage technologies that enable us to secure the governance and ensure that we're privacy compliant. Um, the customer data asset that we have is, is, you know, is extremely valuable as we've talked about in this interview, it's also responsibility. And we take that very, very seriously. And so, you know, Dave, back to your question about, you know, decisions to go, you know, open source or leverage for technologies. So there's always a balance. You know, we, we love to push the, the bounds of innovation and, and we wanna be on the forefront of data, sharing data, science, collaboration for this industry. But at the same time, we balance that with making sure that our technology partners are the right ones, because we are not willing to compromise our governance and our fir and our, our privacy, uh, priorities. >>That's gonna be interesting to see how that evolves. And I, I loved that. Frank was so candid about it. I think the key for any cloud player, including a super cloud is you gotta have an ecosystem without an ecosystem. Forget it. And you see a lot of companies. I mean, we were at Dell tech world. They're kind of, they're at the beginnings of that, but the ecosystems, nothing like this, right. Which is amazing, nothing against, against Dell, they're just kind of getting started and you have to be open. You have to have optionality. Yep. You know, so I, I don't know if we'll see the day where they're including data, bricks, data lakes inside of the snowflake cloud. That will be amazing. <laugh> but you know, you never say never in the world of cloud, >>Do you stranger things, Rosemary and Patrick, thank you so much for joining us talking about what 84 51 is doing powered by snowflake and also the rise of the snowflake retail cloud and what that's doing. We'll have to have you back on to hear what's going on as I'm sure the adoption will continue to increase. Absolutely. Thank you so much to both for having us, our pleasure. You appreciate this for our guests. I'm Lisa Martin. He's Dave ante stick around Dave will be back with Frankman CEO of snowflake. Next. You won't wanna miss it.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, welcome to the Cubes Live coverage of AWS reinvent 2020. I'm Lisa Martin and I have a Cube alumni joining me Next. Aaron Kelly, the GM of product marketing at AWS Aaron. Welcome back to the program. >>Thanks, Lisa. It's great to be here. >>Likewise, even though we don't get to all be crammed into Las Vegas together, uh, excited to talk to you about Amazon Connect, talk to our audience about what that is. And then let's talk about it in terms of how it's been a big facilitator during this interesting year, that is 2020. >>Great, yes, for sure. So Amazon Connect is a cloud contact center where we're really looking to really reinvent how contact centers work by bringing it into the cloud. It's an Omni Channel, easy to use contact center that allows customers to spin up contact centers in minutes instead of months. Its very scalable so can scale to 10 tens of thousands of agents. But it also scaled down when you when it's not in use and because it's got a pay as you go business model. You only pay when you're engaging with collars or customers. You're not paying for high upfront per agent fees every month. So it's really been a great service during this pandemic, as there's been a lot of unpredictable spikes in demand, uh, that customers have had to deal with across many sectors, >>and we've been talking for months now about the acceleration that Corbett has delivered with respect to digital transformation. And, of course, as patients has been wearing fin globally. I think with everybody when we're calling a contact center, we want a resolution quickly. And of course, as we all know is we all in any industry are working from home. So are they. So I can imagine during this time that being able to have a cloud contact center has been transformative, I guess, to help some businesses keep the lights on. But now to really be successful moving forward, knowing that they can operate and scale up or down as things change. >>Yeah, that's exactly right. And so one of the key benefits of connect his ability to very quickly on board and get started, you know, we have some very interesting and examples like Morrisons, which is a retailer in the UK They wanted to create a new service as you highlighted, which was a door, you know, doorstep delivery service. And so they needed to spin up a quick new contact center in order to handle those orders. They were able to do it and move all their agents remotely in about a day and be able to immediately start to take those orders, which is really powerful, you know. Another interesting example is the Rhode Island Department of Labor and Training. Which part of their responsibility is to deliver unemployment benefits for their citizens? Obviously a huge surge of demand there they were able to build an entirely new context center in about nine days to support their citizens. They went from a knave ridge of about 74 call volume sort of capacity per minute to 1000 call on capacity per minute. And in the first day of standing up this new context center, they were able to serve 75,000 Rhode Island citizens with their unemployment benefits. So really ah, great example of having that cloud scalability that ability to bring agents remotely and then helping citizens in need during a very, very difficult time, >>right? So a lot of uses private sector, public sector. What are some of the new capabilities of Amazon connected? You're announcing at reinvent. >>Yeah, So we announced five big capabilities this during reinvent yesterday that really spanned the entire experience, and our goal is to make it better for agents so they're more efficient. That actually helps customers reduce their costs but also create a better collar experience so that C sat could go up in the collars, can get what they need quickly and then move on. And so the first capability is Amazon Connect Voice I D, which makes it easier to validate that the person calling is who in fact, they say they are so in this case, Lee. So let's say you're calling in. You can opt in tow, have a voice print made of you. The next time you call in, we're able to use machine learning to match that voiceprint to know. Yes, it is Lisa. I don't need to ask Lisa questions about her mother's maiden name and Social Security number. We can validate you quickly as an agent I'm confident it's you. So I'm less concerned about things like fraud, and we can move on. That's the first great new feature. The second is Amazon Connect customer profiles. So now, once you join the call rather than me is an agent having to click around a different systems and find out your order history, etcetera. I could get that all surface to me directly. So I have that context. I can create a more personalized experience and move faster through the call. The third one is called Wisdom. It's Amazon Connect wisdom, which now based on either what you're asking me or a search that I might make, I could get answers to your questions. Push to me using machine learning. So if you may be asking about a refund policy or the next time a new product may launch, I may not know rather than clicking around and sort of finding that in the different systems is pushed right to me. Um, now the Fourth Feet feature is really time capability of contact lens for Amazon connect, and what this does is while you were having our conversation, it measures the sentiment based on what you're saying or any keywords. So let's say you called it and said, I want a refund or I want to cancel That keyword will trigger a new alert to my supervisor who can see that this call may be going in the wrong direction. Let me go help Aaron with Lisa. Maybe there's a special offer I can provide or extra assistance so I can help turn that call around and create a great customer experience, which right now it feels like it's not going in that direction. And then the last one is, um, Amazon Connect tasks where about half of an agents time is spent on task other than the call follow up items. So you're looking for a refund or you want me Thio to ship you a new version of the product or something? Well, today I might write that on a sticky note or send myself a reminder and email. It's not very tracked very well. With Amazon Connect task, I can create that task for me as a supervisor. I could then X signed those tax and I can make sure that the follow up items air prioritized. And then when I look at my work. You is an agent. I can see both calls, my chats and my task, which allows me to be more efficient. That allows me to follow up faster with you. My customer, Andi. Overall, it's gonna help lower the cost and efficiency of the Contact Center. So we're really excited about all five of these features and how they improve the entire life cycle of a customer contact. >>And that could be table stakes for any business in terms of customer satisfaction. You talked about that, but I always say, You know, customer satisfaction is inextricably linked to employee satisfaction. They need. The agents need to be empowered with that information and really time, but also to be able to look at. I want them to know why I'm calling. They should already know what I have. We have that growing expectation right as a consumer. So the agent experience the customer experience. You've also really streamline. And I could just see this being something that is like I said, kind of table stakes for an organization to reduce churn, to be able to service more customers in a shorter amount of time and also employee satisfaction, right, >>right that's that. That's exactly right. Trader Grills, which is one of our, you know, beta customers using some of these capabilities. You know, they're saying 25% faster, handle times so shorter calls and a 10% increase in customer satisfaction because now it's personalized. When you call in, I know what grill you purchased. And so I have a sense based on the grill, you purchase just what your question might be or what you know, what special offers I might have available to me and that's all pushed to me is an agent, So I feel more empowered. I could give you better service. You have, you know, greater loyalty towards my brand, which is a win for everyone, >>absolutely that empowerment of the agent, that personalization for the customer. I think again we have that growing demanded expectation that you should know why I'm calling, and you should be able to solve my problem. If you can't, I'm gonna turn and find somebody else who can do that. That's a huge risk that businesses face. Let's talk about some of the trends that you're seeing that this has been a very interesting year to say the least, what are some of the trends in the context center space that you guys were seeing that you're working Thio to help facilitate? >>Yeah, absolutely. So I think one of the biggest trends that we're seeing is this move towards remote work. So as you can imagine, with the pandemic almost immediately, most customers needed to quickly move their agents to remote work scenario. And this is where Amazon Connect was a great benefit. For as I mentioned before, we saw about 5000 new contact centers created in March in April. Um, Atiya, very beginning of the pandemic. So that was a very, uh, that's a very big trend we're seeing. And now what we're seeing is customers were saying, Hey, when I have something like Amazon Connect that's in the cloud, it scales up. It provides me a great experience. I just need really a headset in a Internet connection from my agents. I'm not dealing with VPNs and, ah, lot of the complexity that comes with trying to move on on premises system remote. We're seeing a huge, you know, search of adoption and usage around that the ability to very quickly create a new context center around specific scenarios are use cases has been really, really powerful. So, uh, those are the big trends moving to remote remote work and a trend towards, um, spinning of new context that is quickly and then spending them back down as that demand moves or or those those those situations move >>right. And as we're all experiencing, the one thing that is a given during this time is the uncertainty that remains Skilling up. Skilling down volume changes. But looking as if a lot of what's currently going on from home is going to stay for a while longer, I actually not think about it. I'm calling into whether it's, you know, cable service or whatnot. I think What about agent is actually on their couch at home like I am working? And so I think it's being able to facilitate that because is transformative, and I think I think I'll step out on limbs side, you know, very potentially impact the winners and the losers of tomorrow, making sure that the consumer experience is tailored. It's personalized to your point and that the agents are empowered in real time to facilitate a seamless and fast resolution of whatever the issue is. >>Well, and I think you hit on it earlier as well. Agents wanna be helpful. They wanna solve a customer problem. They wanna have that information at their fingertips. They wanna be on power to take action. Because at the end of their day, they want to feel like they helped people, right? And so being able to give them that information safe from wisdom or being able to see your entire customer profile, Right? Right. When you come on board or know that you are Lisa, um, and have the confidence that I'm talking to Lisa, I'm not. This is not some sort of, you know, fishing, exercise, exercise. These are all really important scenarios and features that empower the agent, lowers cost significantly for the customer and creates a much better customer experience for you. The collar? >>Absolutely. And we all know how important that is these days to get some sort of satisfying experience. Last question. Erin, talk to us about, you know, as we all look forward, Thio 2021. For many reasons. What can we expect with Amazon? Connect? >>Well, we're going to continue to listen to our customers and hear their feedback and what they need, which what we certainly anticipate is continued focus on that agent efficiency, giving agents mawr of the information they need to be successful and answer customers questions quickly, continuing to invest in machine learning as a way of doing that. So using ML to identify that you are who you say you are, finding that right information. Getting data that I can use is an agent Thio. Handle those tasks and then automate the things that you know I really shouldn't have to take steps is a human to go do so if we need to send you a follow up email when when your product ships or when your refund is issued. Let me just put that in the system once and have it happened when it executes. So that level of automation continuing to bring machine learning in to make the agent experience better and more efficient, which ultimate leads to lower costs and better see set. These are all the investments. You'll see a sui continue for it next year. >>Excellent stuff, Erin, thank you so much for joining me on the program today, ensuring what's next and the potential the impact that Amazon connect is making. >>Thanks, Lisa. It's great to be here >>for Aaron Kelly. I'm Lisa Martin. You're watching the cubes. Live coverage of AWS reinvent 2020.

>> Announcer: From around the globe. It's theCUBE with digital coverage of AWS re:Invent 2020, sponsored by Intel, AWS and our community partners. (upbeat music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're coming to you from our Palo Alto studios today with our ongoing coverage of AWS re:Invent 2020. It's a virtual event, like all the events in 2020, but we've been going there since 2013. We're happy to be back this year and we're excited to have for the first time on theCUBE, our next guest, she's Kelly Herod the US SAP Offering Leader for Deloitte Consulting. Kelly, great to see you. >> Great to see you as well, Jeff, thanks so much for having me. >> Absolutely, so first time on, on theCUBE, you guys have a really interesting concept at Deloitte, you call it the Kinetic Enterprise. What is the Kinetic Enterprise all about? >> Yes. So if you think about the past, organizations built their technology infrastructures to be what we would call built to last, the future though is all about built to evolve. And that's exactly what the Kinetic Enterprise is. It's really how we're helping our clients create the right technology infrastructures that evolve with their business. And Kinetic Enterprise is focused on four key pillars. The first, that we're building a technology solution that's clean. That means we want to have reduced amount of custom code or things that we may have built that really rack up your technical debt. The second pillar is that it's intelligent. So we're leveraging all of the technologies, artificial intelligence, machine learning, to really automate and change the way in which an organization runs their business. The third pillar is that it's responsive, and that means it's on the cloud and this is where AWS comes in. And then the last pillar is that it's inclusive. So it uses all of the technologies and microservices available to really optimize and achieve a company's business value objectives. >> So that is a great summary, and I've got the list of the four pillars. It's just interesting you lead with clean. You know, there's a lot of conversation about digital transformation and move fast and be dynamic, you know, would be kind of an opposite to static. But clean, interesting choice of words. It runs with core... Core clean ERP with minimum technical debt. Why clean is such an important thing? I get kind of intelligent and responsive, but clean is an interesting attribute to pick. >> Absolutely, so if you take a step back and think... (Kelly hangs) when comes to ERPs, when ERPs came out, there was... (Kelly hangs) how you're going to run your entire organization on this one solution. What we've found is that as companies have put ERPs, they've gone through and created so much customization, that it's that which makes it very difficult to be able to keep up with technology changes or actually migrate to the next versions. So the concept here is if you're going to go in and put in brand new ERP, such as an SAP S/4HANA, this time around in order to achieve the promise of ERPs, let's make it clean. Let's stick to as much standard functionality as possible within the core, and then we innovate on the edges. And so that will allow us in the future to maintain that flexibility or dynamicism of a Kinetic Enterprise. >> Right. So I have to tease you Kelly 'cause SAP R/3 and ERP is not necessarily synonymous with digital transformation, speed, agility, and embracing change. So you've been involved in Deloitte's SAP practice for a long time. Why should people start to rethink about SAP in terms of being responsive, in terms of being able to change quickly and to your vocabulary, more kinetic? >> And you're right. You know, I've been doing SAP for 20 years. So I actually did start back in the R/3 days. And, you know, I would just say that things are changing, is evolving. You know, SAP themselves has been going through a transformation, a revolution. You look at the ERP landscape as a whole, all of the ERP players are moving to the cloud. The technology is the backbones are changing. Now the reality is, you know, going in and actually changing out your ERP, no matter what solution you're using, it's a big endeavor or undertaking. The goal here, and why we're partnering with SAP, partnering with AWS is really focused on how can we make this more efficient for our clients? More importantly, I like to think about it as how can we make this less of a one and done, and more of a let's keep transforming the technologies and the business as things are changing in the market, along the way. And using technologies to even change how we implement, allows us to do that. >> So, Kelly, another thing a lot of people probably don't think of is SAP and AWS, together in the same sentence. So I'm sure there's a lot of people that are much more intelligent about this, but for those that aren't as familiar, tell us a little bit about the relationship with SAP and AWS and then how you guys are leveraging that at Deloitte. >> Absolutely. So when you... There's a couple of things that I would bring up. One is SAP S/4HANA solutions, in particular, but any SAP environment that you're running on, one of the objectives most of our clients are focused on is how to move to the cloud, and that's where AWS comes in. You can absolutely run any of your SAP solutions on AWS. And what that brings you with is more flexibility, so that you can actually scale or contract your infrastructure that you're running SAP on based on your business needs. The second thing that we've been partnering with AWS to do is a little bit of what I just mentioned, which was a teaser around, how do you change the way you even go about implementing an SAP solution or start to migrate your business? So one of the things we asked ourselves was, could we radically change how you jumpstart an S/4 implementation? And what we decided to do is team up with AWS and leveraging machine learning, artificial intelligence, most importantly, standing up an environment on AWS. We actually created what we call Kinetic Finance Startup. Many of our clients are choosing to start with finance and specifically SAP central finance to begin their journey to the new S/4HANA environment. And what we've been able to do is create a touchless build solution, so over a weekend, we can actually connect to your existing ERP solution. Majority of those is starting with an ECC environment. We can extract the data, we can use harmonization rules to actually change and modify your data and optimize it for the future. And then we actually through completely touchless built-in automation, stand up a brand new AWS environment with S/4HANA on it and actually automate the configuration and testing of the basic financial transactions. So when you come in the next week and we start the conversation with the client, we're actually looking at a real life S/4HANA system on AWS with their mas... >> Oh, that's... >> So the whole concept is to change how we engage. >> Right. So again, I don't know that I were to think of finance as kind of a lead application, to start this journey. I mean, I can see on one hand, it is the system of record and it, you know, it has a lot of very important information that's got to eventually get into finance. On the other hand, it seems like there's less critical, maybe lower hanging fruit that's less risky. Is it because you can run it kind of in a parallel path for some period of time, but it strikes me that finance might not be the first place you go to look for some early wins. >> It's actually what you just said about the parallelism. So the reason we've seen that finance actually was one of the starting points is even if you look at the history of SAP's S/4HANA solution, way back before we got to that, it started with a concept called smart accounting or simple finance. And the theory here is, you could actually... If a company has, let's say multiple ERPs, as most do, you can actually grab the financial information, bring it into a new S/4 or central finance environment, and actually combine or merge the accounting information to get improved reporting, optimize a shared service organization. So it's actually a lower risk way to start the journey before going and touching the heart of the business or core operations, or manufacturing, for example, >> That's pretty interesting. So you run it in parallel for a while and then eventually does, is the plan that it takes over, from the old. So it is effectively kind of, I guess, a slightly delayed lift and shift, or maybe it's a reassemble and then a flip. I don't know how you would describe it because it's not really lift and shift. >> It's not really lift and shift actually, you have two options. You can either over time pull all of your business processes out of the underlying ERP solutions and bring them into the S/4HANA environment or multiple S/4HANA environments. Or some companies may choose to continue to... (Kelly hangs) Especially if you're in an industry where you do a lot of acquisitions or divestitures, you may not have an intention of ever combining all of your ERPs, but you may want to change each of them to S/4HANA underneath, and then have one environment in which you're pulling your data together to really consolidate your financial reporting. >> That's great. I want to follow up on something that you mentioned, which is the use of machine learning and artificial intelligence. And we talk a lot about, right? Those are hot buzzwords all over the place, but, you know, I'm pretty vehement in that, you know, general purpose AI and ML is kind of interesting, but where the real interesting stuff ends is where the rubber hits the road, is in applied. And it sounds like you've got a pretty interesting application where you're applying this technology to help make this move to cloud go a little bit smoother. >> Yes. One of the areas, you know, since we've been talking a bit about finance then I'll use it as an example. Is if you think about it, whenever we go in and we're typically working with... (Kelly hangs) especially in finance, you know, one of the topics is, how to optimize a chart of accounts? So over time we've done this hundreds of times, if we can look at different sectors, different industries, we can use benchmark chart of accounts. So instead of making this a paper-based exercise that individuals are doing, why not take that and actually use artificial intelligence machine learning to create data harmonization rules, so that technologies can actually do that same work. And so that's been one of the things we've been working on that I personally find very interesting just in my finance background. >> Right. And is this a relatively new thing, or have you guys been doing this for a while? >> Actually, it's something that over the last 12 months, we've been focused on building out in partnership with AWS. So it's fairly new. >> That's great. I want... I'd love to shift gears a little bit, and talk about COVID, and the impact of COVID on your business. Clearly in March, right? It was the light switch moment and everybody had to work from home and it was a quick rush to make sure that everybody was safe and we could support our remote workers, that said, can't help with the ba... All the bad stuff that's happening in hospitality and travel, and a whole lot of other industries. So that aside and that's bad stuff. In the tech industry, we were able to make the move, but now we know we're six, seven, eight months into this thing, and it's clear that, you know, we're going to have many elements of this going forward for a while. So I'm curious just from your business and your customer point of view, if you can share, you know, kind of the contrast of what happened in March and April to what you're seeing now and how this new reality, whatever this new reality is going to be, as we, you know, continue to evolve is impacting this digital transformation conversations? >> It is interesting. So if I pivot back to March, when this all occurred, you know, it truly did feel an instant going from in-person. And as consultants we travel and typically have a Monday through Thursday, or Monday through Friday type of travel schedule to an instant working from home overnight. And, you know, I'm really proud of our teams and how they seamlessly made that transition. Many, including myself, were actually leading clients through final cut overs in parallel to this happening. And we were able to really pivot and make those shifts, and I was reflecting with one of the executives I worked with, you know, she and I, you know, six months later, we're looking back at how we did that and how impressed we were with what the team pulled off. And since then, they've been able to do several other go lives, which is great. But I think that it was something we had to do quickly. I think many would have said it couldn't have been done that you would see the whole world move to a working from home environment, but we did. What it tells me is it gives me a lot of hope for a lot of the things that businesses can do in the future. In the past we used to constrain ourselves of, Oh, there's no way we could ever get XYZ done, or we can't make this type of change in the world, but we can. If I flash forward to now, I think we're very settled in kind of this new way of working, but I'm also hopeful for what the future is going to look like. I don't believe it will be a pivot all the way back to... Especially for consultants traveling on a regular basis of Monday through Friday. Instead, I think we're going to create models that give people and organizations the flexibility they need to really balance some of their personal responsibilities along with their work responsibilities. My hope and expectations is that also opens up options so that all organizations have access to more talent that they may not have had before. And I think that also means global talent. I think we're showing we can work as global teams, which means, you know, I could now have members from Japan joining, you know, my permanent leadership team in ways that I maybe never have thought of before. Those are just some examples of what I expect and hope for all of us that we'll see coming out of this. >> Hopefully and I know... Like you said, you've been a consultant for years and years and years, and you guys spend lots of time on airplanes, and hopefully you don't have to spend quite so much time on airplanes because you don't necessarily have to be there all the time. But you talked about an interesting thing and that's talent and opening up the opportunity to get more talent that maybe you wouldn't have ever considered. And along those same lines, right? Is the move in diversity and inclusion. And I just watched a show that you did a few months ago, called the... "A Chance for Change: Accelerating Business Recovery, Through Gender Diversity," on a Facebook interview, very cool panel, really enjoyed it. And I want to follow up on some of those things, 'cause you've made some really simple and poignant points. And one of the things that you said definitively, go back to the wide diverse talent and perspective equals winning in business, period. I love that. You know, we hear this all the time that, you know, not only is it the right thing to do, but it's also good for business. And isn't it nice when those two things can actually line up. And you just talked about, you know, in more of a generic sense, the ability to open up your talent window when there's a worldwide talent shortage, both for geography, but also the work in diversity and inclusion and to continue to hold the momentum that continues to build in this area. I wonder if you could, you know, kind of share your thoughts on that, and your position and what's going on with Deloitte. >> Absolutely. You know, I do think this is one of those key pivotal moments for all of us, and I believe we have, coming out of this an option to really move the needle on our diversity and inclusion, and equality efforts. You know, one example I think about women, women in leadership positions. You know, being in consulting, you know, one of the challenges has always been that we do travel a lot, and it can be difficult to balance all the responsibilities, professional and personally. I think with a move to more flexible work arrangements, less travel, or travel for purpose is what I would highlight for the future. I think it opens the door to many more women being able to have careers in consulting, if that's what they, you know, had desired. I also think it allows them to have... You know, spend their entire careers in consulting and in ways we never saw before. And that means you'll see as significant movement and women in leadership positions. I also think this applies to underrepresented minorities. I hope that from all of this, instead of there may be companies that focus on recruiting from, you know, schools that are local to them or within their surrounding areas. I think this gives us an opportunity to really open that aperture up and look at talent from any school or university, or geography, and being able to get the right skill sets in the door and the right talent. Therefore you can actually see movement and diversity within teams, as well as at the leadership levels for URMs. >> Right. Right. And really managing to the right things too. I think that's the other thing that's coming out of this, and we've had a lot of conversations on work from home or work from anywhere. You guys are a little bit different than the consultant 'cause your team is there, usually local at the client site for some period of time. But for a lot of people, it's the first time they are not sitting across from a desk or, you know, within close proximity. Now you too, in your teams. And so, the shift changes that now you have to judge output, (Jeff chuckles) and not activity. And you would think that that would be a great and easy thing to execute, but we're hearing more and more that it's not necessarily. And you really highlighted, I think, three leadership traits that are always important, but more important now than ever before in that other interview. And I just want to call them out 'cause I thought it was worth calling out. You know, empathy has never been more important. Resilience, and my favorite one you said at the end, calm in the storm. I just wonder again, if you could share, you know, kind of, as you've gone through it, both, you know, as somebody at Deloitte within the greater Deloitte group, but then also in managing your own teams, to maintain that calm in the storm and to maintain, you know, empathetic leadership, because I think you've said it before, right? This is a personal challenge that we're all going through. We all have different things going on at home, whether it's the spouses working, the kids are doing homeschool. People are taking care of older parents, this and that. It's a real personal thing, and so these leadership characteristics, these softer leadership characteristics have never been more important >> That's so true. And, you know, when I think about the empathy part, right now what we're going through is also about how is each of us as leaders also sharing a bit more about how we're experiencing this? I think the sharing of stories is what also helps many on the teams adapt, adjust. The reality is when you're working on camera all day and, you know, in the past, imagine that you maybe were having a tough day or you weren't feeling that great, you weren't on camera all day with every one of your coworkers. You we're actually, you know, sitting in an office, you may have to go to the conference room to do some meetings, but you didn't look... (Kelly hangs) like someone was kind of staring at you all day long. Now, when we're working from home virtually and we're on Zoom or Skype or WebEx, et cetera, all day, it does feel like you're under the lights when you're on camera. And there's a lot of pressure and people are trying to figure out how to manage their own emotions while doing that. And, you know, my message would say as an empathetic leader, it's okay for you to also share when you might be having a tough go that day. Maybe one of your children has been kind of acting out and they didn't really want to do the virtual school. It's okay to share in that because everyone's going through it, and it makes us all more human. >> Right. >> And it makes us all more connected. >> Right. Well, I will share with you a pro tip, we've done a few of these interviews and it is okay to let people turn off the camera. And I think as a manager, I think it's actually an okay thing to say, okay, everyone, let's just turn off our cameras and get a break from that camera that's got that eye on you all the time, because it is just another, you know, kind of a factor that we have to deal with. Well, go ahead. >> And I was going to ask, what do you actually, you know, I don't know what one of your techniques is, but I know mine is some of the meetings, it's actually just go back to traditional telephone calls (Jeff chuckles) and actually even just being on your cell, put on your air, you know, your earbuds, or your headphones and even walk. >> Right. >> So I think the other thing we're all missing is actually that movement, the steps to go to the coffee maker and back, or to lunch and back, we don't have them anymore. So you've got to work extra hard, actually getting those extra steps in calories and just mental breaks at times. >> Yeah, well then there's a whole another tranche on walking during meetings. And I used have a boss that I would only do one-on-ones while we took a walk. He always says, I get in there... 'Cause then there's, you know, you're not necessarily looking at each other. And if there's some sensitive things or tough conversations, sometimes it's easier if you're not just looking across the table at one another with all the silence. So there's a lot to be said for that as well. Well, Kelly, I really enjoyed this conversation and getting to meet you for the first time. It sounds like you're doing a lot of cool and exciting things and, you know, exciting speed and innovation with SAP, that's noble work and I'm sure a lot of people are really happy to have you help them out there. So thank you very much for your time and to have a great AWS re:Invent. >> Thanks, Jeff. It was great to discuss this with you. >> Absolutely. All right. She's Kelly, I'm Jeff. You're watching theCUBE's ongoing coverage of AWS re:Invent 2020. Thanks for watching. We'll see you next time. (upbeat music)

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Hey, welcome back everyone. Cubes coverage here in San Francisco, the Moscone South. We're here at the RSA conference. I'm John, your host and the cube. You know, cybersecurity is now a global phenomenon, but cubbies have to move at the speed of business, which now is at the speed of the potential attacks. This is a new paradigm shift. New generation of problems that have to be solved and companies solving them. We have a hot startup here that's growing. Hazel cast, the CEO, Kelly Kelly Harrell is here. Cube alumni. Good to see you. Good to see you, John. Hey, so we know each other you've been on before. Um, you know, networking, you know, compute, you know the industry. You're now the CEO of Hazel cast. So first of all, what does Hazelcast do? And then we can get into some of the cool things. Hazel cast is an in memory compute platform. >>So we're a kind of a neutral platform. You write your applications to us. We sit in front of things like databases and stream, uh, streaming sources, uh, and we execute applications at microsecond speeds, which is really, really important as we move more and more towards digital and AI. Uh, so basically when, when time matters, when time is money people buy Hazelcast. So I've got to ask you your interest in better, you can do a lot of different things. You can run any companies you want. Why Hazelcast what attracted you to this company? What was unique about it that got your attention and what made you join the firm? Well, when I first started looking at it and realized that a hundred of the world's largest companies are their customers and this company really was kind of kind of a run silent run deep company. A lot of people didn't know about it. >>Um, I could not, I had this dissonance, like how can this possibly be the case? Well, it turns out, uh, if you go into the Java developer world, the name is like Kleenex. Everybody knows Hazelcast because of the open source adoption of it, which has gone viral a long, long time ago. So once I started realizing what they had and why people were buying it, and I looked at that, that problem statement and the problem statement is really increasing with digitalization. So the more things are speeding up, the more applications have to perform at really, really low latency. So there was this big big growth market opportunity and Hazel CAS clearly had the had the drop on the market. So I've got to ask you, so we're at RSA and I mentioned on my intro here the speed of business while he's been down the, it kind of cliche moving at the speed of business, but now business has to move as the speed of how to react to some of the large scale things, whether it's compute power, cloud computing, and obviously cyber is attacks and a response. >>How do you view that and how are you guys attacking that problem? Well, you know, it's funny. I think the first time I truly understood security was the day that I was shopping for a home safe. You know, because I realized that all of these safes, they all were competing on one of the common metric, which is the meantime to break in, right? Is that you had one job and all you can tell me is that it's going to happen eventually, you know? So the kind of the scales got peeled off my eyes and I realized that, that when it comes to security, the only common factor is elapsed time, you know, and uh, so the last time is what matters. And then the second thing is that time is relative. It's relative to the speed of the attack. You know, if I'm just trying to protect my goods in a safe, the last amount of time is how long it can take for the bad guy to break into the safe. >>But now we're working at digital speeds, you know, so, you know, you take a second break that down to a thousand, uh, that's uh, you know, milliseconds. It takes 300 milliseconds. The blink. Yeah. Now we're working at microsecond speeds. Uh, and we're finding that there are just a really rapidly growing number of transactions that have to perform at that scale and that, and that speed. Um, you know, it, it may have escaped people completely, but card processing, credit card, debit card processing, ever Dawn on you that that's an IOT application now. Yeah, because my phone is a terminal. Amazon's a giant terminal number of transactions go up. They have three milliseconds to decide whether or not they're going to approve that. And uh, now with using Hazel Cassady not just handle it within that three milliseconds, but they also are running multiple fraud detection algorithms in that same window. >>Okay. So I get it now. That's why the in-memory becomes critical. You can't gotta be in memory. Okay, so I got to ask the next logical question, which is okay, I get that it makes less sense and I want to dig into that in a second. But let's go to the application developer. Okay, I'm doing dev ops, I'm doing cloud. I'm cool. Right? So now you just wake me up and say, wait a minute, I'm not dealing with nanosecond latency. What do I do? Like what's I mean, who's, how to applications respond to that kind of attack velocity? Well, it's not a not a a an evolution. So the application is written to Hazel cast is very, very simple to do. Um, there are, uh, like 60 million Hazel cast cluster starts every month. So people out in the wild are doing this all day long and we're really big in the Java developer community, but not only Java. >>Um, and so it's very, very straightforward with how to write your application and pointed at Hazelcast instead of pointing at the database behind us. Uh, so that part is actually very, very simple. All right, so take me through, I get the market space you're going after. It makes total sense. You run the, I think the right wave in my opinion. Business model product, how you guys organize, how do people sign up for our development and the development side? Who's your buyer? What's the business look like? Share a Hazel. Cast a one-on-one. Yeah. So we're an open core model, meaning the core engine is open source and fully downloadable and you know, free to use, uh, the additional functionality is the commercial aspect of it, which are tend to be features that are used when you're really going into, into sensitive and large scale deployments. Um, so the developers have access to a, they just come to hazelcast.org and uh, and join the community that way. >>Um, the people that we engage with are everyone from the developer all the way up through the architect and then the a C level member who's charged with standing up whatever this new capability is. So we talk up and down that chain, um, where you're a very, very technical company. Uh, but we've got a very, very powerful RLM. What's the developer makeup look like? Is it a software developer? Is it an engineer? So what's the makeup of the, of the developer? They're core application developers. Um, a lot in Java, increasingly in.net, uh, as a MLM AR coming on, we're getting a lot of Python. Uh, so it's, it's developers with that skillset and they're basically, uh, writing an application that they're, um, uh, basically their division is specified. So we need this new application. It could be a new application for a customer engagement and application for fraud detection and an application for stock trading. >>Anything that's super, super time sensitive and, uh, they, they select us and they build on us. So you get the in-memory solution for developers. Take me through the monetization on the open core. Is it services? Is it, uh, it's a subscription. It's a subscription model. So, okay. Uh, w we are paid on a, on a annual basis, uh, for, for use of the software. And um, you know, however large the installation gets is a function that basically determines, uh, you know, what the price is and then it's just renewed annually. Awesome. We'll do good subscriptions. Good economics. It is. What about the secret sauce? What sun in the cut was on the covers? Can you share what the magic is or is it proprietary? Is that now what's, uh, it's, it's hardcore computer science. It really is what it is. And that is actually what is in the core engine. >>Um, but I mean, we've got PhDs on staff. We're tackling some really, really hard problems. You know, I can, I can build anything in memory. I can make a spreadsheet in memory, I can make a word processor and memory. But you know, the question is how good is it? How fast is it, how scalable, how resilient. So, um, you know, those, you're saying speed, resilience and scale are the foundation and it took the company years and years to be able to master this. That's an asymptotic attempt and you're never at the end of that. But we've got, you know, the most resilience, so something, it doesn't go down. It can't go down because our customers lose millions for every second that it's down. So it can't go down. It's got to scale. And it's gotta be low latency number of customers you guys have right now. Can you tell us about the public references and why they using Hazelcast and what did they say about it? >>Yeah, I mean we've got a hundred of the largest, uh, financial services, about 60% of our revenue. E-commerce is a, another 20% large telcos. Another job. There are a lot of IOPS type companies, right? Yeah. Basically it's, um, so you know, in the financial services, uh, it's all the names that you would know, uh, every logo in your wallet. It's probably one of our customers as an example. Um, massive banks, uh, card processors, uh, we don't get to talk about very many of them, but you know, something like national bank of Australia, uh, capital one, um, you know, you can, you can let your, your mind run there. Um, our largest customer has over a trillion dollar market cap. There's only a few that meet that criteria. So I'll let you on that one. One of the three. Um, all right, so what's next for you guys? >>Give the quick plug in. The company would appreciate the insights. I think he'd memory's hot. What do you guys are going to do? What's your growth strategy? Uh, what's, what do you, what's your priorities? The CEO? Yeah. Well, we just raised a $50 million round, which is a very, very significant round. Um, and we're putting that to work aggressively. We just came off the biggest quarter in the company's history. So we're really on fire right now. Uh, we've established a very strong technology partnership with Intel, uh, including specialty because of their AI initiatives. Because we power a lot of AI, uh, uh, applications. IBM has become a strategic partner. They're now reselling Hazelcast. Uh, so we've got a bunch of, uh, a bunch of wind in our sails right now coming into this year, what we're going to be doing is, uh, really delivering a full blown, uh, in memory compute platform that delivers, that can process stored and streaming data simultaneously. >>Nothing else on the planet can do that. We're finding some really innovative applications and, um, you know, we're just really, really working on market penetration right now. You know, when you see all these supply chain hacks out there, you're going to look at more in memory detection, prevention, counter strike, you know, all this provision things you got to take care of. Mean applications have to now respond. It's almost like a whole new SLA for application requirement. Yeah, it is. I mean, the bad guys are moving to digital speed, you know, if you have important apps that, uh, that are affected by that. Right. You know, you'd better get ahead of that. Well, actually you could be doing that, by the way. You can be doing that on your, on premise or you could be doing in the cloud with the managed service that we've also stood up while still we get the Cuban in, in memory Africa and when we were there, I will be happy. Kelly, congratulations on the funding. Looking forward to tracking you. We'll follow up and check in with you guys. All right. Congratulations. Awesome. Thanks John. I appreciate it. Okay. It's keep coverage here in San Francisco, the Moscone. I'm John furrier. Thanks for watching.

>>from our studios in the heart of Silicon Valley. Palo ALTO, California It is a cute conversation. >>Hi, and welcome to the Cube studios for another cube conversation where we go in depth with thought leaders driving innovation across the technology industry. I'm your host, Peter Boris. Digital businesses affecting every enterprise of every size, small and large, and the types of solutions that required the types of outcomes that are being pursued are extremely complex and require an enormous amount of work from some of the best and brightest people on the business side as well as the technology side. And that means not just from a large company. It means from an entire ecosystem of potential sources of genius and insight and good hard work. So the consequence for every enterprises, how do they cobble together that collection of experts and capabilities that are gonna help them transform their business more successfully, Maur completely and more certainly than they would otherwise? And that's we're gonna talk about today. Today we're here with Kelly Ireland, who's the founder and C E o. C. B Technologies. Kelly. Welcome to the >>Cube. Thank you, Peter. Happy to be here, >>so let's start by finding a little bit about CV Technologies to also about what you do. >>Um, I have a IittIe background, so I have been in it for 40 years. In 2001 I decided I had a better idea of how to both support clients as well as my employees. So I opened CB Technologies were value added reseller, um, and then say about five years ago, I decided to do some transforming of the company itself. I saw what was going on in the industry, and I thought this was the time for us to get going. Turned out we were a little early, but we wanted to transform from what you would call it the value added reseller two systems integrator. Because that was the only words what they had for. You know what that end result would be? Now I've heard it's the, um, domain expert integrator, which we like a lot better. And what we've done is gone from this value add, which we've all seen over the last couple of decades, into actually engineering solutions, and mostly with consortiums, which will talk about of the O. T. I t. Convergence and what's going to be needed for that to make our customers successful. >>Well, you just described. In many respects, the vision that businesses have had and how it's changed over years were first. The asset was the hardware. Hence the var. Today, the asset really is the date of the application and how you're going to apply that to change the way your business operates the customer experiences, you provide the profitability that you're able to return back to shareholders. So let's dig into this because that notion of data that notion of digital transformation is especially important in a number of different names, perhaps no more important than in the whole industrial and end of things domain. That intersection of I t know Tia's, you said, Tell us a little bit about what you're experiencing with your customers as they try to think about new ways of applying technology technology rich data to their business challenges. >>We'll use the perfect word you said dig, because this is all about layers. It's all about it was technology and software. Now it's about technology, software and integration. In fact, the conversations were having with our clients. Right now we don't even talk about a no Yim's name. Where before you would. But we haven't our head. What? We know what would be best. What we look at now is the first thing you do is go in and sit down with the client. And not only with the client, the you know, the executives or the C I or the C T. O's et cetera, but the employees themselves. Because what we've seen with I I I o t o t i t Convergence, it's You have to take into account what the worker needs and the people that are addressing it that way. Um, this project that we started with Hewlett Packard Enterprise, they started up what we call the refinery of the future. It could be acts of the future. It doesn't really matter. But it was getting at least up to five use cases with a consortium of partner companies that could go address five different things within the refinery. And the reason that I think it's been so successful is that the owner, the CEO Doug Smith and the VP of ops Linda Salinas, immediately wrap their arms around bringing employees. They're a small company there, maybe 50. They brought half of them to HPD Lab to show them what a smart pump laws for their chemical plant text. More chemical in Galina Park in Texas. Starting from that, it was like they put him on a party bus, took them down, put them in the lab, told them, showed them what a smart pump was and all of a sudden the lights turned on for the workers. These are people that have been, you know, manual valves and turning knobs and, you know, looking at computer screens they'd never seen what a smart, censored pump waas all of it sudden on the drive back to the company, ideas started turning. And then HP took it from there, brought in partners, sat everybody in the room, and we started feathering out. Okay, what's needed. But let's start with what the client needs. What do those different business users within the chemical plant need, and then build use cases from that? So we ended up building five use cases. >>Well, so what? Get another five years cases in a second? But you just described something very interesting, and I think it's something that partners have historically been able to do somewhat uniquely on that is that the customer journey is not taken by just an individual within the business. What really happens is someone has an idea. They find someone, often a partner, that can help them develop that idea. And then they go off and they recruit others within their business and a local partner that has good domain expertise at the time. And energy and customer commitment could be an absolutely essential feature of building the consensus within the organization to really accelerate that customer journey. If I got that right? >>Absolutely, absolutely. And what we saw with Refinery of the Future was getting those partnerships HP East started. It created the project kind of through information out to many of their ecosystem partners trying to gain interest because the thing was is this was kind of our bet was a very educated bet, but it's our bet to say, Yeah, we think this makes sense. So, you know, like I said, I think there's about 14 partners that all joined in both on the I t om side the ot oh am side and then both Deloitte and CB Technologies for the S. I and like expert domain expert integration where you really get into How do you tie OT and I t together? >>All right, so we've got this situation where this is not As you said, It's not just in the refining process, manufacturing businesses. It's in a lot of business. But in this particular one, you guys have actually fashioned what you call the refinery of of the future has got five clear use cases. Just give us an example of what those look like and how you've been RCB technology has been participated in the process of putting those together. >>Um, the 1st 1 was pretty wrapped around Predictive Analytics, and that was led by Deloitte and has a whole host of OT and I t integration on it >>again, not limited to process manufacturing at all >>at all, but and a good group, you know, you have national instruments, Intel flow. Serve. Oh, it's ice off Snyder Electric, PTC riel, where they're such a host >>of the >>consortium and I I think what was most important to start this whole thing was H P E. Came in and said, Here's an MOU. Here's a contract. You all will be contract ID to the overall resorts results. Not just your use case. Not just one or two use cases you're in, but all five because they all can integrate in some sense so >>that all can help. Each of you can help the others think. Problems. Truce. That's the 1st 1 about the 2nd 1 >>The 2nd 1 is video is a sensor that was Intel CB Technologies. I think we have as you're in there as well, doing some of the analytics, some P T. C. And what that was all about was taking video. And, you know, taking a use case from Linda and saying, Where where do you need some sort of video analytics Taking that processing it and what we ended up doing with that one was being able to identify, you know, animals or aggressive animals within the train yard. A downed worker transients that shouldn't be there because we can't decipher between you know, someone that's in text marks p p ease versus somebody that's in street clothes. So taking all that analyzing the information, the pictures, training it to understand when it needs to throw and alert >>lot of data required for that. And that's one of the major major drivers of some of the new storage technologies out there. New fabrics that are out there. How did that play? A role? >>As you can imagine, H p E is the under underlying infrastructure across the entire refinery. The future from compute with the, uh, EJ data center into the Reuben network into nimble storage for storing on site. Um, what we're finding, no matter who we talked to in the industry, it is. Most of them still want to keep it on Prem. In some sense, security. They're still all extremely cautious. So they want to keep it on Prem. So having the nimble storage right in the date, having the edge data center having everything in the middle of this chemical plant was absolutely a necessity. And having all of that set up having my team, which was the C B Tech team that actually did all the integration of setting up the wireless network, because guess what? When you're in a different kind of environment, not inside a building, you're out where there's metal pumps. There's restrictions because ah, flash could cause an explosion so intrinsically safe we had to set up all that and determined how? How could we get the best coverage? Especially? We want that video signal to move quite fast over the WiFi. How do we get all that set up? So it takes the most advantage of, you know, the facility and the capabilities of the Aruban network. >>So that's 12345 quickly were >>three worker safety, which hasn't started yet. We're still waiting for one of the manufacturers to get the certification they need. Um, four we have is connected worker, which is on fire, having a work >>of connected worker on fire and worker >>safety. >>Yeah, they don't sound, but just think of all the data and having the worker have it right at his fingertips. And, oh, by the way, hands free. So they're being ableto to take in all this data and transmit data, whether it's by voice or on screen back >>from a worker central perspective, from one that sustains the context of where the worker is, what stress there under what else? They've got to do it said. >>And and what are they trying to complete and how quickly? And that's where right now we have r A y that's in the 90% which is off the chart. But it's and and what's great about being at Text Mark is we actually can prove this. I can have somebody walk with me, a client that wants to look at it. They can go walk the process with me, and they will immediately see that we reduce the time by 90%. >>So I've given your four. What's the 5th 1? >>Acid intelligence, which is all about three D Point Cloud three D visualization. Actually being able to pull up a smart pump. You know it really? Any pump, you scan the facility you converted into three D and then in the program that we're using, you can actually pull up a pump. You can rotate it 360 degrees. It's got a database behind it that has every single bit of asset information connected videos, cad cams, P and I. D s. For the oil and gas industry. Everything's in their e mails could be attached to it, and then you can also put compliance reports. So there you might need to look a corrosion. One of those tests that they do on a you know, annual or every five year basis. That's point and click. You pull it up and it tells you where it sits, and then it also shows you green, yellow, red. Anything in red is immediate, attest that tension yellow is you need to address it greens. Everything's 100% running. >>So the complexity that we're talking about, the kind of specificity of these solutions, even though they can be generalized. And you know, you talked about analytics all the way out to asset optimization Intel intelligence. There are We can generalize and structure, but there's always going to be, it seems to us there's going to be a degree of specificity that's required, and that means we're not gonna talk about package software that does this kind of stuff. We're talking about sitting down with a customer with a team of experts from a lot of different places and working together and applying that to achieve customer outcome. So I got that right >>absolutely, and what we did with the consortium looking at everything. How they first addressed it was right along that line, and if you look at software development, agile following agile process, it's exactly what we're doing in four I I o T o R O T I t Convergence, because if you don't include all of those people, it's never going to be successful. I heard it a conference the other day that said, POC is goto I ot to die, and it's because a lot of people aren't addressing it the right way. We do something called Innovation Delivery as a service, which is basically a four day, 3 to 4 day boot camp. You get all the right people in, in in the room. You pull in everything from them. You boot out the executive team partway through, and you really get in depth with workers and you have them say what they wouldn't say in front of their bosses that this happened with Doug and Linda and Linda said it was mind blowing. She goes. I didn't realize we had so many problems because she came back in the room and there was a 1,000,000 stickies. And then she said, the more she read it and the more you know, we refined it down, she said it was absolutely delivered, you know, the use case that she would have eventually ended up with, but loved having all the insights from, >>well, work. Too often, tech companies failed to recognize that there's a difference between inventing something and innovation. Inventing is that engineering act of taking what you know about physics or social circumstance Secreting hardware software innovation is a set of social acts that get the customer to adopt it, get a marketplace to adopt it, change their behaviors. And partners historically have been absolutely essential to driving that innovation, to getting customers to actually change the way to do things and embed solutions in their operations. And increasingly, because of that deep knowledge with customers are trying to doing, they're participating. Maurine, the actual invention process, especially on the softer side of you said, >>Yeah, yeah, I think what's really interesting in this, especially with Coyote. When I look back a few years, I look at cloud and you know everything was cloud and everybody ran to it and everybody jumped in with both feet, and then they got burned. And what we're seeing with this whole thing with I o t you would think we're showing these are lies, return on. Investments were showing all this greatness that can come out of it and and they're very slow at sticking their toe in. But what we've found is no one arrives should say the majority of corporations anymore don't want to jump in and say, Let's do it two or five or $10 million project. We see your power point. No, let's let's depart Owen with with what we're doing, it's, you know, a really small amount of money to go in and really direct our attention at exactly what their problem is. It's not off the shelf. It's but it's off the shelf with customization. It's like we've already delivered on connected worker for oil and gas. But now we're are so starting to deliver multiple other industries because they actually walk through text mark. We could do tours, that text mark. That was kind of the trade off. All these partners brought technology and, you know, brought their intelligence and spent. We were now on two years of proving all this out. Well, they said, Fine, open the kimono will let your customers walk through and see it >>makes text mark look like a better suppliers. >>Well, it's enhanced their business greatly. I can tell you they're just starting a new process in another week. And it was all based on people going through, you know, a client that went through and went. Wait >>a minute. I >>really like this. There are also being able to recruit technologists within the use in industry, which you would think text marks 50 employees. It's a small little plant. It's very specialized. It's very small. They pulled one of the top. Uh, sorry. Lost not. I'm trying to think of what the name >>they're. They're a small number of employees, but the process manufacturing typically has huge assets. And any way you look at it, we're talking about major investments, major monies that require deep expertise. And my guess is the text Mark is able to use that to bring an even smarter and better >>people smarter and better. People that are looking at it going they're ahead of the curve, for they're so far ahead of the curve that they want to be on board were that they're bringing in millennials on they're connected. Worker Carlos is there trainload lead. And he dropped an intrinsically safe camera and it broke and he tried to glue it together, tried to super glue it together. And then he ran back to Linda and he said I broke the case and this case is like £10. They call it the Brick. They gotta lug it up. They got to climb up the train car, leg it up, take a picture that they have sealed the valves on all the cars before they leave. Well, he had used the real where had, you know, device. And he went into Linda and he said, I know there's a camera in there. There's camera capabilities. Can I use that until we get another case? And she's like, Yeah, go ahead. Well, he went through, started using that toe like lean over, say, Take photo. We engineered that it could go directly back to the audit file so that everybody knew the minute that picture was taken, it went back into the audio file. This is where we found the process was reduced by 90% of time. But he turned around and trained his entire team. He wasn't asked to, but he thought, this is the greatest thing. He went in trainable. And now, about every two weeks, Carlos walks in to my team that sits a text mark and comes up with another use case for connected worker. It's amazing. It's amazing what you know were developed right out of the customer by using their workers and then, you know, proactively coming to us going. Hey, I got another idea. Let's add this where I think at version 7.0, for connected worker. Because of that feedback because of that live feed back in production. >>Great story, Kelly. So, once again, Callie Ireland is a co founder and CEO of CB Technologies. Thanks for being on the tube. >>Thank you for having me >>on once again. I wanna thank all of you for joining us for another cute conversation. I'm Peter burgers. See you next time.

>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey, welcome back everyone! It's theCUBE's live coverage, day two, of three days of wall-to-wall coverage. Keynotes, amazing announcements, great vibe here. Again, 52,000 people here at Amazon re:Invent, I'm John Furrier, my co-host Dave Vellante, we're here again, 6th year, just an amazing amount of content, two sets Eron Kelly is the General Manager of the Enterprise Services Marketing Basically part of marketing for Lilac Groups a lot of the areas. Great to have you on theCUBE. Thanks for spending the time! >> It's great to be here John and Dave, I really appreciate it. >> Alright so, how hard is your job? (all men laugh) I mean we were just doing an analysis of Andy's keynote and there's so much to talk about you have so many things under your purview. You have a broad portfolio of Amazon services It's really crazy good for you guys, the business is going great, highly profitable How do you do it all? How do keep track of it? What's your favorite child? Tell us >> It's a great point, there's so much going on and the speed and the pace of innovation but it's exactly what builders are looking for, right? They want to be able to come to AWS and not have to compromise. Because they want to see every tool that they need for every job And so for me I have a pretty broad portfolio I've really been excited this week about a lot of our compute announcements, right? So our announcements around our new instance family with A1 based on some custom silicon AWS Graviton processor Really excited about that Bringing the Arm community to the Cloud for the first time, we're jazzed about that one. >> And that motivation there is lowering costs for Arm-based apps, right? >> It's really two-fold, right? It's bringing the Arm community to the cloud It's the first time we've got an Arm processor in a large Cloud provider, so giving them that scale-up, elasticity, pay-for-what-you-use kind of model but then the second thing is lowering costs for customers for scale-out workloads so things like web tiers containerized microservices and you know in the general purpose area customers, we think they can save up to 45% which is meaningful, so we're really excited about that. That's been a really neat announcement a neat project we've been working on for a while. I would also say in the area of Compute We've added 100GB networking to a couple of our Instance types. C5n based on Intel processors and that's really been the workhorse in the HPC community and now with 100 GB of networking we're going to be able to do even more processing, more power, more advanced scenarios there And it's kind of an interesting dialogue, right? The more data you have, the more compute you need and it creates this virtuous cycle and one of the gaps was networking, so bringing 100GB It really allows those Intel chips to run >> Well, Big Data guys are going to eat that up to, I would think I mean, the links between Big Data and HPC become clearer >> Exactly right. >> Talk about the latency thing Andy talked to me last Monday about this I had a long conversation with him about it Latency matters, you guys listen to customers. Networking, you mentioned a key part of the flywheel Compute storage networking obviously morphing with the Cloud while you guys are optimizing and raising the bar. How are you guys handling the latency question? Because this comes up a lot You got the On-premises piece now you guys are doing things in the Cloud How do you market that service? How do you handle the latency? Talk about the role of latency in the portfolio. >> There's a couple things in there The first one, what I would highlight is Latency within an HPC environment or a machine learning environment and so that's where again this 100GB networking has been really powerful. We've also announced a new networking feature or protocol, Elastic Fabric Adapter which actually allows you to go even faster now in some networking scenarios, which is particularly interesting, again, in HPC So we've really worked hard in reducing the latency throughout the data centers for these higher end compute scenarios. >> Well, you have the custom silicon I wanted to just take you through this because EC2 has always been great, but setting up an Instance could take 10 seconds. Lambda now you can do it in hundreds of milliseconds. By having the custom silicon, How does that impact the network stack? Because I would imagine that the performance gains on having kind of a custom silicon around EC2 and the Compute, would be a gamechanger for running things under the covers, for instance, like a Vmware or managing security boundaries issues, what's the... >> So we made these investments a few years ago with the Nitro system, Where we took a look at the current Instance environment and said hey if we can offload some of that computer networking to a purpose-built chips on those cards we can actually free up more capacity for those processors to run faster and give you more value basically for each Instance type. So that was part of the beginning of Annapurna Labs and the Nitro system was offloading this networking into those custom built chips. That's the start and then what we've done is the Nitro system has allowed us to innovate much faster So we've added three times more Instances this year than last year because we're building on the Nitro system Graviton processor is just one more example We've added new processors from AMD And of course we've continued to advance with our Intel chip set as well. >> Talk about, I just want to just change gears for a bit Because you're in product marketing Executive General Manager Andy talks about the new way the culture at Amazon Old guard, new guard... Traditional product marketing, you can take a product you can bring it to market, waterfall it out at the beach and then you do all the activities How do you raise the bar in your job where you got to go out and take not just products, this is services now so you have a series of, a lot of services How does that change how you do product marketing? And how's that different from people who might not know how you guys operate? Talk a little about the culture of product marketing at Amazon. >> Sure, yeah. So I would say first and foremost it's all about education, right? So we really want to make sure that whenever where there's a new service that comes out we're super clear on what does it do what is the benefit and how can customers take advantage of it. And we're trying to position it in a way We like to say internally, sort of a non-technical CIO can understand So whenever you look at a new service You look at our detail pages. We put a tremendous amount of rigor and clarity We make it very simple, make the value pop clear I think the second thing we're starting to do and we're seeing it reflected in our products as well Is how can we tell more aggregated stories? So today during the Keynote, You saw Andy talk about abstractions, right? And one of the first ones he mentioned was Control Tower, which is one of my products So I got a little passionate around it. But what's interesting about that is that customers are coming to us and saying OK, I love the AWS, I love all these tools I love the granularity of managing things at a certain level and setting policies at a certain level But you guys have thousands, millions of customers running AWS, what's the right way to set up my environment? Can you give me a blueprint to do it? To set it up and run it in a very secure and compliant way. So Control Tower is a great example of a both a service that helps you do that as well as a marketing message that says Hey, let's look at this now in totality Let's you set up these environments faster based on best practices and now you can control in a much easier way. >> So you're basically trying to simplify the message so it's not speeds and feeds >> Well, what I would say is we want to simplify the message so that everyone can understand but we don't want to lose track of those builders those tinkerers that get in there, they want the speeds and feeds, they want the nobs and part of their differentiation as a developer is understanding all the details So we want to have both. >> It's also trying to help people figure out what to use where. As your portfolio grows and grows and grows the complexity becomes amazing for some people And Tailgate helped me figure out mapping to my workload, what to use where what's the best cost solution sometimes it's hard to figure that stuff out, isn't it? >> Yeah, well, it's again, it's this balance between We want to be able to provide the right tool for the right job I think Andy had a nice analogy today in the Keynote Where he talked about building fixing a house with just a hammer, right? And instead you're going to want to have that right tool for that right job And so part of our job in Product Marketing is making it very clear When do I use this particular Instance type versus this versus this? What are the trade-offs? And that's a key part of our job. >> And that resonates with people because there's a lot of redundancy in tools, too in the marketplace, people, a lot of them have the same tool the same hammer and you guys have a variety of services. So the question I got to ask you though As you look at the services and Amazon's role here at the event How would you summarize what's going on here? Because there's so much, Andy had a slide up there that said "Signal from the noise" and that's our phrase Extracting the signal from the noise which is kind of fun, but you have so much signal this noise and there's too much signal how would you encapsulate, for someone watching, what is happening this year? Where is Amazon for customers? What's the positioning? How should they think about, you mention builders? How would you summarize what the action is going on here? >> Right, so I would talk about it like this First and foremost, I would say we're adding more capability and building the broadest and deepest platform so that builders can always, they never have to compromise they always can find the right tool they need for the right job. So first and foremost, that speed of innovation that pace of innovation is continued and if there was one message that people should take away is Wow! They are still innovating like crazy they have an amazing amount of technology and so I don't have to compromise when it comes to datalinks. So that's kind of the first main message. Then I think the second thing I would say which kind of follows on that is OK but we also recognize that we've got a lot of services and now we need to start to build some services that bring these together and again Control Tower is a great example of that Lake Foundation is a great example of that for datalinks. And so that's sort of the second thing we are starting to create services that are abstraction layers that bring together a lot of the details to solve very specific problems. The third thrust that I would highlight is just the amazing focus around machine learning and AI and just how that has been such a key investment area for us and such a key ask for our customers and our mission there is to just democratize it. We want every builder to able to bring machine learning and add it to their solutions. And the number of services you saw announced today in the keynote as well as some earlier this week and last week just shows that our commitment and focus on that >> And extending EC2 to support some of that stuff >> Exactly right >> And the training and the like >> I'm a Star Trek fan so I always go to Scotty Scotty, more power! You guys are bringing more power to the table with each Compute and these abstractions. I want to get your thoughts on something that I talked with Andy about in depth last week before the show, and we were riffing on this notion of a new kind of Developer emerging and he talked about in the keynote, a new persona of developer, A new kind of developer is emerging. And he also kind of talked about net new workloads I wrote about it in my stories on SiliconANGLE in the forums about it, which is this all this goodness going on at the abstraction layer with a lot of horsepower enabling things that were hard to do. AI's a great example AI's been around since I was in college in the 80's and 90's and now it's rose up with power What are some of those persona developers look like? How do you look at that net new workloads? What's your reaction to that? Because this seems to be a big trend that's not your old school developer banging out code now there's OpenSource communities, we got that but in the working day and life of companies people are building apps. What's this new persona developer look like? >> Well, there's different personalities, right? There's the core tinkerer like you talked about there's now the data scientist that's coming in and taking advantage of these machine learning tools. You have kind of a cloud administrator that's kind of trying to look across everything and they want to build as well, right? They don't just want to sit there and manage the dashboards, they want to build as well and so we're seeing that in some of those personas. of course, app developers is another big part of it. >> Now you could talk to Firecracker too, right? >> We could talk a little bit, yeah >> So I met with Adrian yesterday and of course people used to poke at Amazon a lot hey, what about Open-source, you guys giving back to Open-source? And so Firecracker explain that and sort of what you guys are doing there and specifically in Open-source? >> So that's a great example of where we had some technology, and what Firecracker is it's a container for microservices that can run in a non-virtualized environment and we've used it as the underpinning for Lambda and Fargate And we looked at it and we said you know what? We want more people to be able to take advantage of this because it's about saving money it's about improving security. And so we decided to open-source it. And so that was one of our announcements on Monday was open-sourcing Firecracker and making it available to the community and so we're really excited about it. >> One of the things I want to ask you as we wrap up here, first of all great job on all the work you've done at Amazon impressive to see the level of services >> Thank you! That you guys are announcing and it's become a competitive advantage and you've got a great trajectory a lot of learnings and as Andy says there's time compression for experience and time which is good for a competitive strategy but as you look forward to 2019 What's your plan? What are your goals? How are you going to raise the bar? The term you guys use a lot. What's your goals? What are you trying to accomplish? >> You know the number one thing that we spend our time on is listening to customers and saying what's next? What do you need next, right? 90% of our innovation comes from customer input and so now we got a new wave of services we're introducing we're going to spend time with customers they're going to give us feedback we're going to make those services better and then we're going to find new places where they want us to go so next year is going to be just as exciting as this year and next year when I see you guys here we're going to be talking about a whole new wave of things coming out, it's been fun. >> You're certainly running hard and the other thing I've noticed in learning how Amazon works and getting deeper under the covers there you got a growing field, great professional services and a sales force that is not trying to grab the wallet from the customer you guys have a long game perspective >> That's right >> Carla, had a great conversation with her about this you have to service that How are you going to enable these guys You mentioned education earlier this is a big part of your plan, right? The integration with the field how does that work? You going to provide the messaging all the tools...how..cuz that's grow you've got to service that What's your perspective on the field >> Oh for sure, you're highlighting my Q1 goals right now It's really important to dial up that connection because as we get more and more services our field sellers, what's great about our field teams is that they're so aligned to customer needs So they don't carry specific quotas on individual products and things like that they're really focused on hey, what do ya need? And how can use the full portfolio to help you out? And so part of our challenge as a product marketer is not only educating customers on our products but educating the field on our products and which ones are most viable for which scenario and so that's a big part of our focus as well within the product marketing function is hey how do we really nail these scenarios very crisp, very compelling both for the customer and field seller to say ooh I saw that pattern in a customer! Let me go bring this technology forward and talk to them about it, so really excited about next year and you hit on something else that I think is really important which is this long term view, is our sales teams have always taken a long term view with customers they're not sitting there at the end of the Quarter trying to, you know, close the deal it's all about that long term view And it's allowed us to make some of these investments we've had, we've made >> You guys also use your own technology too I noticed a lot of the different groups You've got all the goodness of Cloud. You got to use some of that tech You've probably got some machine learning waiting around the AI bots and all kinds of cool tools you're integrating in dog-fooding or what do they call it? >> I mean, the reason why we're able to add so many services every year is that we build on our own platform, right? So you can have a very small team we talk about the two pizza team A very small team is able to build these services because they use AWS and in its entirety. And so it's very very exciting as these things get connected Like last week we talked about a predictive auto-scaling, so one of the features Auto-scaling's been a pretty popular feature over the years where people can scale up and scale down a large fleet of EC2 Instances but now we've added machine learning to that where it will now predict when the scaling should happen. So it allows you to scale up your EC2 Instances ahead of time based on historical patterns. So there's ML coming into everything we do. >> And server-less is booming too you know, that's going to be a big part of your focus by the way, you mention the Fleets I love this, we haven't talked about it much on theCUBE, but this notion of fleets is pretty powerful Having just a bunch of fleets of servers ready to go >> Ready to go and being able to manage across the different pricing models is also very, very powerful. I want to really ramp up very very quickly take advantage of those spot instances in those moments with really big cost savings as well as ramp back down >> Hey, keep adding functionality keep removing all the barriers lowering the price, making it high performance and I love that business model a lot of companies don't have that so Congratulations! >> You know, we just always want to add more we want to give customers more tools so they can have the right tool for the right job we want to give them the most powerful platform so they can do the highest end things as well as give them scenarios where hey, it's a little bit lower cost and it's for smaller workloads we don't want to overpay and be over-provisioned that's a key part of our strategy. >> I want it all and I want it now >> That's right! >> Well, you did a good job on the messaging Andy wants to mention builders and right tool for the job I think there's a drinking game going on on that he mentioned multiple times Congratulations Eron Kelly, Thank you! >> Thanks John and Dave, Really appreciate your time on theCUBE. >> General Manager Amazon Product Marketing here inside theCUBE, breaking down what's going on, what's his goals how Amazon keeps up with the pace Good insight I'm John Furrier, Dave Vellante Stay with us for more coverage after this short break. 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>> From the Hard Rock Hotel in Las Vegas, it's theCUBE, covering HoshoCon 2018. Brought to you by Hosho. >> Okay, welcome back everyone, we're here live with theCUBE in Las Vegas, for the first security conference. It's an inaugural event. It's called HoshoCon. This is where security experts are gathering to discuss the future. I'm John Furrier, host of theCUBE. With Joe Kelly, he's the co-founder and CEO of Unchained Capital. We were just talking about the old days, and big day, yeah? Joe good to see you, thanks for coming on theCUBE. >> Good to see you too John, thanks for being here. >> So, take a minute to explain what Unchained Capital is. We heard some people talking this morning, earlier, about your business model, love it. Take a minute to explain what your business model is, what you're doing that's different. >> Sure, so, Unchained Capital, we're really a financial services company, I'd say. Kind of in this new era where we have this challenge of users have crypto currency, they want custody of their assets themselves, they want to maintain some of the grave sovereignty over and control over their money. Not just give it, relinquish it wholly to a bank or someone else. So it's an interesting time to start a business like ours. Our first product is loans. We give out dollar loans, in U.S. dollars, to individuals or businesses who provide crypto currency as collateral. So right now, we accept Bitcoin, or Ethereum as that collateral. And we do accept it in a fully custodial manner today. When you get a loan from us you are sending us your Bitcoin, you're trusting us to keep it safe, and we do. But we also have some more multi-signature models that we'll be releasing soon, that we work with, for instance, Hosho here on getting our smart contract, and Ethereum honored it for doing such a thing with Ethereum. But we're really trying to find ways to bridge that gap of user don't have to quite give up everything , we don't have to have full control, we can still as a lender, safely extend money and know that we can. >> So you've got a lot of couple things going on. >> Yeah. >> You've been topical here at this conference, been hearing in the hallway, there's been sessions on it around custody, >> Yeah. >> So that's one big issue that everyone's talking about, but it's also now your lending. So, this collateral, that's services, financial services, so it's a little bit fin-tech meets cyber security needs. >> Yeah. >> You're in the middle of two cross-hairs. >> Yeah. (John laughs) >> How are you guys doing this? >> I mean, I think, as far we were talking about earlier, my co-founder and I kind of cut our teeth in the big data technology space, and learned a lot through that. And learned a lot especially about how easy it is to get caught up in either a hype, or a market cycle, where you don't pay as close attention as you should to customers, and what they need. We went through a pivot in that business, which was good, the right thing to do, but we wanted to start this company consciously in a way that we didn't have to pivot. So there always has been this kind of focus on the customer, the end user, and what they want. >> Hey, building a sustainable business. >> Building a sustainable business. >> With paying customers, what a great idea. >> Yeah, who would've thought. (both laughing) >> Well turns out it was a good call because with the whole bubble burst thing, you know in February really, I think February to me was the month where you saw the decline, the security token, Rightfully so is the discussion for all the utility all the stuff regulating now, so a little bit of a dark time for us, but, the winners coming out of this will be the durable real builders. >> I think so, yeah. You know we didn't, we chose not to do token sale last year, to our, maybe in the long run it could be a bad idea but we still feel pretty good about it. >> It's a good cause. >> Yeah. >> SCC reported today, I saw it today, SCC is actually having some ICO's give money back on violations. >> As they should, yeah. >> So, you would have been properly optimizing your time on other non-company building activities? >> Yeah. >> Yeah, running around Asia managing token prices >> Now, it's a shame, its like these small teams run out like 12 or 20 people almost running public companies, in terms of the demand and opinions and-- >> Yeah, and they're young, they got keep their eye on the ball, which is the value proposition evolution and also security. >> Yeah. >> Alright, so talk about how, what you're doing here? Why're you here at HOSHOCon, I see they're a supplier, a partner with you guys. >> Yeah. >> But what's, what's the story here for you guys? >> So we got to know Hosho earlier this year, we spent about six months developing a theorem smart contract. So a theorem, it doesn't have a native multi-signature mechanism, there's no way that within the protocol you can speak to the protocol in a way that says, you need multiple signatures to make this transaction valid. Unlike BitCoin that has that multi-signature spelled out. So, and we, with the way we store the currency, we store it all cold storage, we store it with multiple hardware devices, and in so, we believe the only way to do that, or the only way to store cryptocurrency is with that, and with multi-signature enabled. So, to try to-- >> To minimize the risk on the custody side. >> To minimize the risk of, yeah, on the custody side. Also, you minimize risk of theft, you also create some resiliency in the sense of maybe a key is lost, like you got some back up keys to it. So, really important to get to that multisig status but as you maybe saw last year, with hacks like there's a parody multisig wall that was hacked to the tune of some hundreds of millions of dollars. There's several of these multisig contracts people developed that were really sophisticated pieces of software allowed ownership to be transferred or things to change, within the contract that, in our opinions kind of, didn't need to be there, and put the contract at risk. And so we worked on this very simple, bare bones, smart contract that does multisig as closely as, it's already spelled out in Bitcoin. And worked with Hosho on at that, it's been since honored it twice. Both times, passed with flying colors. No issues, not a single discrepancy. >> You did the work up front? >> Did the work up front, yeah. >> That's critical. >> Really smart team of folks that put that together and so yeah we're very security conscious company. We like being present, contributing to conversations like those that are here. >> It's funny, we were talking earlier in some interviews it's like, security is a differentiated of some of these exchanges. (Joe laughs) >> We got better security >> Cheap table steaks. I mean, differentiate? That's like standard. Alright, so talk about how someone uses your service because I think this is fascinating. A lot people are holding crypto, they may or may not want to sell it. There's also fluctuation risks. >> Yeah. >> So how does this system work? I give you my crypto and you lend me money? >> Yup. >> Is it that simple? >> Yeah, so you first sign up to our website. We lend mostly in the U.S., a few international jurisdictions, but as long as you're in a jurisdiction we can lend, you finish out your profile with us. We do do a KYC email check on all folks and then you put in a loan application. And within that loan application, we can either lend you at a 35% loan to value or a 50% loan to value. You have a slightly better interest rate on the lower LTV. What that means is, if you'd like a $100,000 loan, say, you need to provide maybe $200,000 of that collateral up front, in the form of Bitcoin or Ethereum. We can fund loans and you can go from basically a new account and application to a funded loan, in like four hours even. You have that time from the client signing up to us, wiring the money and so that, that, can be a pretty fast process. Which is really unlike any other loan products. Even if you get a unsecured loan on a website, like an Earnest.com or some of these, it can take you many days, a week or more sometimes to close the loan. >> So you're taking a big risk with this, you guys do? >> Well you could say that. I mean, I mentioned that-- >> It all depends on the fluctuation, right? >> 50% on LTV. We do do margin calls, so if there's a 25% price drop, we'll issue a margin call. It means, with the client is required to post more collateral or else we can declare the loan in default. Luckily we've had no defaults, we've never had to force a liquidation over anybody-- >> So explain a margin call real slowly, so okay, it drops below a certain point percent. Let's say 25? You do a margin call, they don't come up with more collateral, to refuel essentially the collateral. You can default, which means you take ownership of the crypto? >> Yup, in that case we would take ownership of the crypto currency. We would sell what portion of it, was need to pay off the principal of interest, and then they get the remainder. But ya, thankfully nobodies ever fully bailed on us in that way. >> Ya, not yet, not yet. Well so for me this is a great service. So, great for people who get some hands on some, some fiat, some cash. Now, on the backhand, I'm only imagining just my brain spins around, you got a lot of hedging going on, you got have math, a lot of math behind it. Maybe, it's big data. How are you managing the back end, because now in your risk profile, so you the margin call, you got some mechanisms, which is great. What's going on in the background? You crunching on some cloud computing, Amazon computing, going OK, where are we with our positions? There must be some math involved. What's going on behind the curtain? Can you tell us a little bit? >> I think you'd be surprised, I think that, we've been able to manage pretty well, with just more puristic and common sense around a lot of this stuff. I think what we did up front before we even, gave our first loan, did a lot of research on historical volatility with Bitcoin. Looking at, ok, what are the most significant drops within a day, or a week long period and, based on that analysis that's where we did come up with this sort of 50% LTV ceiling for us. That says, really? You know, 9.9999 or 99.99% of the time, you will never see anything that big within a day. Maybe a week, there's been a couple of weeks where Bitcoin will go down 50%, in that period but that's, that evolves on like a human reactionalary kind of time scale. Not something that you're-- >> Well today the stock market dropped 800 points today and Bitcoin didn't move. So that's good that there's no corelation. >> Yeah. >> But the point is, you're measuring it. So, is there, the question next question I have for you, as I'm thinking about myself if I was a customer. If I was a customer, do you provide like some sort of total cost of ownership calculative, that I would have to know, okay, 'cause I want to plan, I don't want to be defaulted. Right, so I should have a good understanding of how to manage it so I give you guys some crypto, for the loan. >> Yeah. >> I got to have some reserves. You guys see a formula for that, is there benchmarks or is it more of ad hoc general. >> Yeah, it's definitely, I mean it's a case by case basis but with every client. We recommend not of course leverage all your crypto currency, you want to leave some in reserve for margin call and it just depends on personal situation and how much-- >> And the margin call too, if they give the money back, that's fine too right? So either pay back the loan-- >> Yeah, exactly. Or pay down the principal, which you can do partial payment, we have no prepayment penalty. So pay down some principal, or yeah, post more collateral. Just some way to get that ratio back. >> Got it, cool, how's business going? >> Good, yeah. We think it's been a great year for us, the first half was pretty bananas honestly, just with the kind of bull run and taxis and stuff like that. Summers been a little slower, but we're still full of-- >> Tax season, yeah roll your eyes. Hey, welcome to the tax bill. >> Yeah! >> Trading all that crypto. >> Yeah. >> People had a wake up call. >> Well, it's arguably what killed all the volumes. It's finally when people realized, oh my gosh, you know, I can't 1031 moving forward, I have to pay taxes every time I trade all client for another all client. I think that really dampened volume this year. >> Alright, so I got to ask you, what's going on here, in this event thats folks that didn't make it, what is some of the conversations, a lot of diverse, smart people here. Kind of core kernel industry security, but it's not just security nerds, it's total laid out players on the security side to business we had Andre on talking about custody. You've got you're business here, financial services chain. What's some of the hallway conversations that you're over hearing and that you're been involved in? >> Let's see. I mean, almost just been in, you characterized it pretty fairly I think, there's real engineers here. People that kind of get into base with over the pros and cons of the different programming language, or implementation for smart contracts. So, it's kind of, a definitely more nerdy conference. I haven't heard of one, like ICO I should buy into or anything like that. >> Thank God! >> Pretty nice. >> That's refreshing. >> Yeah. >> I mean an ICO converse, a little bit over, a little long on the tooth there, don't you think? >> It's a converse we deserve. (John chuckles) That's just a tagline. >> Yeah. >> Alright, so what are you seeing as the major trend that's going to bring back, not bring back, but establish more of a mainstream culture with crypto, because you're actually getting into the level of services that certainly for the early adopters and insiders that are been there from the beginning, or involved now making money and having crypto, to Joe Sixpack, out there, who's really, he's interested in, it's really the younger generation love this/ You can't pull a 16 year old away from. >> Right. >> Learning how to mine, getting involved and pretty much anyone under 30, pretty much, is on the crypto band wagon. >> Yeah. >> It's a revolutionary, kind of cultural shift. >> Especially in our customer base, very well over represented there. >> So, how does it get more mainstream? >> I mean I think speaking somewhat biasedly, you know, part of our view is that, we're a company that's here to make crypto currency more valuable in the long run, to it's holders. Not necessarily, doesn't have to be in dollar terms be more pricier, but the idea that before us, before other people doing these kind of loan business, there's really nothing else you could really do with your Bitcoin. You could buy it, you could hold it. And then go sell it later, or you can give it to someone else, kind of trade it for fact or feeling here and there. You could trade it for other off coin. >> Convoluted process though. >> Yeah, all these things. And there, don't have much to do with your daily life. Except for, if you buy a car maybe, and that person will accept Bitcoin, and things like that. But, our clients are buying homes, they're investing in real estate, they're investing in businesses, and paying off credit card debt. Things like this, so. >> What are some of the sample loan sizes? What's the average coming in? >> Well average is $120,000. >> What's the largest? >> Largest is over a million. Yeah. >> Where you guys getting the cash from? >> We have some investors, including some small credit funds, and institutions, high net worth individuals that have pledged to back loans from us. >> So financial pros would get the collateral gain? >> Yeah, totally, you really got to be comfortable with Bitcoin as an asset to then be comfortable with the kind of rates we're talking about here. 'Cause many traditional lenders, they want 20%, 30%, I don't care, it's the riskiest asset there is. Like, they just don't get it. >> So you're building a company, you're a company builder, pragmatic, which is good, but also you got to manage the waves that you're on. Which is high growth and potentially, so you're managing growth. Funding, vision, what's, how is the execution plan, what's the tactical execution plan for you guys? >> I mean, it's interesting. I think, we're talking about getting back to the big data conversation, we really started that, it's a joke that, but smartest thing we do was start that company at the time we did. That, no matter what kind of happened or steps that missed execution, we were on kind of that wave. So, in some ways that formed our philosophy here. But, so you start a business at the right time, and a good space, don't let valuable long term business and let's focus on clients. For us that meant, grow the value of, and the utility of crypto currency is that people are already holding. So, make crypto currency really into the most useful assets in the world. As they should be. They're software, we know they can do more things then what they have done for us necessarily in the last 10 years. So, going forward, I mentioned the loan products we have, we have some storage in custodial technologies we've got, that we will be releasing soon. Things that help you keep crypto currency safe, while consuming products like a loan from us, so. >> And you're based in Austin? >> Yeah, based in Austin. >> How many people on the team? >> 16. >> So a small team. >> Yeah, growing. >> Great, congratulations. >> Thanks John. >> And if I need a loan, I'll come knocking on the door. >> Give us a call >> Regrowning capital. Cube's growing like crazy, going international. >> I like it. >> Going crypto. Joe Kelly, co-founder and CEO of Unchained Capital, check him out. This is theCUBE, bringing you live coverage here at HOSHOCON in Las Vegas. The first security watching conference in the world. We'll be back with more after this short break. (digital music)

(upbeat music) >> Announcer: From the SiliconANGLE Media Office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> Hi, and welcome to a special presentation of CUBE Conversation. I'm Stu Miniman and we're here in our Boston-area studio, happy to welcome to the program first-time guest Brian Kelly, who's the Co-founder and CEO of CLoudGenera. Brian, thanks so much for joining me. >> Stu, thank you so much for having us here. >> All right, first of all Brian, we always love. We get you know a co-founder on the program, you got to bring us back to kind of the why. You know, why was CLoudGenera formed? We've had a chance to dig into it but CLoudGenera, there's cloud in the name, there's generation. Tell me about the company, the name, and a little bit about your background. >> Be glad to. So like most great companies, our company was born of the market's necessity. We saw trend happening as many businesses we're shifting the way they manage their IT and the trend took the form of this buzzword cloud. And so you know CLoudGenera as a company absolutely helps businesses figure out their most efficient path towards leveraging cloud technologies. But our value proposition is actually greater than that. Our business exists to help companies determine the best IT services to support the needs of their organization. >> Great. Well luckily cloud's simple. Enterprise IT, we just have a button we press, and everything works awesome. I think the reality is though, nobody ever gets rid of anything. Changing applications is really tough and it's a really complicated and super fast changing market out there. So maybe, drill in just a tiny bit and explain what it is that you do and why that's a little bit different than some of the other things happening in the marketplace. >> Sure. Well the big easy button does exist, when you push it nothing happens. Maybe it makes a funny sound. As the name would suggest, CLoudGenera specializes in the formation of clouds and to the point that you made, this is not simple, this is not easy. Cloud is not a target state. Unlike virtualization, which was a target state, cloud is really an operating model. And also as you highlighted, there's so much variability and complexity associated with cloud. Am i talking about infrastructure? Am i talking about platforms? Am i talking about software as a service? Cloud for us can be any of those things. It can be you managing your infrastructure. Can be somebody else managing your infrastructure, all the way up through your apps. And so what our business aims to do is to demystify all the variability and complexity associated with making cloud decisions. Really it's about helping people figure out where to place their workloads and what we commonly see is that the migration does not generate success unless you've considered how to optimize your workloads in advance of selecting a new execution venue. So as a business our software, our technology, helps customers to determine how do I optimize my workloads, regardless of whether or not I'm going to move them. And ultimately, how do I get the best value for my spend at IT services as I'm contemplating cloud as a model for hosting my apps? >> Yeah, so every vendor I talk to out there, if I'm a cloud platform vendor or if I'm an infrastructure vendor, they all have these tools that say hey, here's how the experience is going to be on our platform. Maybe it compares against a couple of things out there but you're not pushing hardware, you're not pushing platforms. Explain how you fit into kind of the ecosystem and you're not just, when you say cloud it's it's not just public cloud, it's you know, talk a little bit about the spectrum of things that you support. >> Okay, be happy to. So first, what I would say is that when you look at a vendor strategy, their strategy is to drive you to adopt their technologies, their solutions. And so any of the tools that they're bringing to market, any of the services that they're bringing to market, are biased towards the outcome that they're trying to achieve. This was actually when I say CLoudGenera was born of the market's necessity, the market really needed a solution that was agnostic and unbiased to the outcome. Something that would be so bold is to recommend not doing anything if that was the best option available to your business. That's really what makes CLoudGenera special. We are the best place to go in the market to get that unbiased agnostic viewpoint that's tailored to your needs as an organization and guides you to the right vendors and the right solutions. >> Yeah. It's interesting you think about like there's consulting companies that would get involved and send a bunch of people and help you through your journey. We talked about there's been lots of tools out that have poked at this but there's a big elephant in the room and it's a little tough to kind of figure out where to start. So I just want to, talk a little bit about kind of the breadth and depth of what you do. How do you keep up with all of these things? I mean, while we were talking I'm pretty sure Amazon released one or two new features. And the next time Intel comes out with a spin, you've got a billion SKUs that you have to update. So how does this impact you and how do you help keep up with it? >> So Stu, this is really what creates the longevity and value proposition for my business. The market is changing at breakneck speed. To your point, the major providers both in data center as well as in cloud have probably released a half a dozen new services for the market to contemplate just in our conversation. So CLoudGenera addresses this in a couple of different ways. But all of it born in automation and intelligence. And so we have a cloud research function as a part of our platform that is continually ingesting the data around what the market can offer. So this could be services you could consume from public cloud providers like the Microsoft Azure, the Amazon EC2, the Google Compute as an example, but we're not an infrastructure play. We actually move up and down the stack. So if you want to look at platform as a service solution like Cloud Foundry as an example, you're moving towards no SQL, as an example, for managing data. Do I do that is infrastructure? Do I do it as a platform, as a service? Right, what level of service is available in the market? Our automation, our intelligence, gathering that market data is the big value for our customers because through that automation we give them something that have avoids their need to spend a lot of money on consultants or to spend a lot of time internally trying to assess what the market can offer. And then most importantly once you have that data, how do you turn it into insights? How do you take that data and make it actionable for your business based upon your needs and the requirements of your workloads? So that that's a big part of our secret sauce. A big part of our IP. We stay current with the market so that you don't have to. And what's interesting about our business is that we don't just do point in time comparisons. In fact, we sit on historical data and trends, both how you can modernize in your data center and how you can leverage cloud services and that data set is over four years large, I like to say, not four years old. And so in that way we can even predict where the market is headed so if you're if you're leveraging us or doing this manual as opposed to leveraging our automated methods, we've got the recipe of how to make good decisions and really it is staying current on the market. That's the only way that that you can address it. Love to touch on another aspect of the question you asked, which is consultancies. If there's one thing that we're disrupting in the market, it is the ability to do this analysis at scale. Many of our clients tell us that it's cost prohibitive to hire an army of consultants to come in and assess their current capabilities and then attempt to map that to what the market can offer. If you're using a manual method powered by labor, you're likely going to have an answer that reflects the market ninety days ago, 180 days ago. CLoudGenera gives you the power at your fingertips to get those sort of insights immediately. And when I talk about disruption, it's really doing in minutes what normally took months. it's also a fraction of the cost, Both productivity and labor as well as the true costs if you're leveraging consultants to do this sort of analysis. and so in that way we can scale to servinG customers that are as large and as complicated as the Global Five. We can also scale far and wide to serve many customers in the market at the same time. Again, it's because we're using algorithms. We're using data science. We're not trying to solve this problem with labor. >> Yeah, I love that and you talked about, it's not just about the platform, you're looking at what we've said for years. Customers need to look at their data, they need to look at their applications, and that's where you need to start. I'd like you to talk a little bit about your users because you know, talked to so many companies, it's like oh, they've tried either building their own in-house solution or going to a service provider or going to a public cloud and they get one or two apps. Some critical one or some real important or some cool new one and then they're like okay, I've got hundreds or thousands of other apps and trying to figure out how they do that, you got to use some intelligence. You need to use some, you know, it needs to be driven by software. It can't be some big process that I'd have some consultancy or a thing like that. Do you have some customer examples you can bring us through or talk to how that typically works? >> Yeah, absolutely. I'll share a few patterns that we see in the market. One pattern and it doesn't have a bias towards a particular industry vertical or a particular size of customer. But there's an illusion out there in the market that you'll be able to lift and shift your workload from your data center to Amazon's data center, as an example, and then magically that's going to take care of all your problems. Amazon's going to manage your mess for less. Well, the harsh reality that customers are finding is that while Amazon, as an example, might be an excellent provider of IT services for your business, if you're not optimizing your workload to leverage that provider, you're not going to get the benefits that you'd hope. And so one trend we see commonly in the industry and it's a mistake we hope folks make, whether they leverage our service or they solve this problem some other way, is you know please don't try to do the lift and shift. In fact, another big trend we see in the industry of companies that have gone that route is they do what we like to call repatriation. Where they made the full-fledged push into migrating their workloads to a new venue and ultimately to figure out that the lift and shift was not successful for them. And the larger the client, the more pain they've experienced because the more money they're spending on IT and the harder that gets. >> Just to poke at that a tiny bit and I know we don't have a lot of time to dig into it but it's if you lift and shift and that's the step one of doing, I need to break something apart, I want to refactor some pieces, and eventually know I'll get there. But is that okay and are there paths to get there? Or are you saying hey, you want to sort those pieces out first before you get to the cloud? >> There's some use cases where lift and shift absolutely has a benefit, absolutely has a value. If you're dedicating IT capacity and it's dedicated towards something that's used sporadically, well just the usage model alone, you could potentially get a benefit out of a lift and shift. You're getting the benefit of the optimization just by being able to leverage the elasticity of cloud. But beyond some of those low hanging fruit use cases, we actually see this as a detriment to many company's success. I like to use the analogy of a moving company. The last thing you want to do is pack the box, pick up the box, move the box, and then move it three or four times before you actually get to the destination. That's what lift and shift is really doing. You just pick up what you had in your data center, you put it in somebody else's data center, and now you're in a foreign land and you're going to try to break that thing apart and re-engineer it there. That's actually going to be a lot harder in practice than what we've seen as more of a better option, which is optimized where you are. If you're if your target state for the next innovation is to get to containers, figure out how to containerize before you make the migration as an example. If your endgame is to move from a database on infrastructure to a platform as-a-service, well optimized that databases deployment, optimize that workload before you attempt to transition it to the path. So I would say nine times out of ten, you're probably going to want to treat an application workload before you attempt to move it someplace else. Otherwise, you're just going to be lifting and carrying that box several times. >> Yeah, it unfortunately reminds me of anybody that's moved and you know, you move someplace and three to five years later you run across that box and you're like why did I even move this to my environment. I've outgrown it, I don't need it. I could have either gotten rid of it or done something else with it. Last piece of the technology I want to cover for today is we've talked a bunch about the public cloud, you do a lot with service providers and with the in-house data center stuff. Maybe talk a little bit as to what you cover. Public clouds, there's a few really big ones but there's so many service providers. What do you engage with? What do you cover there and in the data center there's just, I can't imagine how many options there are. What's the scope of what you cover? >> So this might be a little controversial for some folks because if you read the the trade rags, cloud is the answer. Whatever cloud may be, moving to cloud is the answer. Our philosophy as a company is that public cloud is not the only game in town, nor will it be the only game in town in the future. We believe in companies investing in technology to get the best value for their spend. And as a result there's a continuum of options that we see existing far into the future and those include regional data center providers. Frequently we see them being value-added because they can offer a level of service that's not yet been implemented in public cloud. Who's going to manage the stuff that an Azure doesn't manage, as an example. These regional providers, these service providers, many of whom are evolving to do managed services and other people's data centers, not just their own, are going to play a key role in this next wave of technology. And so again, these regional providers, we see them being very important for delivering the service level that customers expect. There's also and this is a very prominent topic right now, there's concerns about data privacy and data sovereignty. While the hyper scalars have done a great job of building a global footprint, they still have gaps. And so if companies are concerned about GDPR in Europe, as an example. If they're concerned about PIPEDA up in Canada, as an example. These regional service providers have the compliance capabilities, they have the protection already in place to not just deliver a high service level but also to deliver a solution that can be lower risk for your business. And so that's really where we see service providers fitting in the market and we see customers having the right mix of public cloud and service provider powered infrastructure. As well as for large companies, they may still have the buying power, and they may still have the level of expertise in house, so like my Fortune 50 clientele but you could even take it down probably to the Fortune 500. Where it's more cost-effective for them to still operate in their data center. Today, because we're a data-driven company and we live in the data and the insights it provides, still the majority of the workloads, either for service level security or if you're a large company, the economics to run IT are still better suited in data center. We don't know that it's always going to be the majority in your data center. We see this evolving as the public cloud providers continue to mature, over the last few years they've matured greatly. But again, we see a continuum of options for customers to consider. We think those options will get smaller but we still think you're going to have a purpose to consider in your data center, in a regional service provider, as well as considering a hyper scalar for your needs. >> All right. Brian, last thing. Need to get speeds and feeds on CLoudGenera. How many employees you have, how many customers you have. Can talk anything about the funding? And tell us about this looking south. >> The Silicon South. Well, let me start there. One of the things we're very proud about is being a company that's headquartered here on the East Coast and specifically in the South. That said, we're already a global company. We have customers around the world. There's well over a thousand subscribers of our cloud assist technology, which is where you can both model future uses of technology as well as load in your existing inventories and analyze your business at scale. What I would share again about the Silicon South is that we're one of these cool companies that is helping the southeast kind of rise up as a technology center. Not one of the normal places that folks think of as innovation hubs but very much in the Carolinas in particular, we have a market that's on the rise with very smart data scientists, very smart developers, and very strong business leaders. And so that's one of the things we are very proud of as a company. There are 22 employees in CLoudGenera today. As I mentioned, we have a global footprint in terms of customers. I gave you a stat just around our cloud assist product. One of the cool things about us is that we serve both the consumer, so that would be the enterprise that's trying to figure out what to do with their technology investments. We also serve their suppliers. We will not bias ourselves so they can't bias the output of our software but what they can do is leverage our software to guide their customers decisions. In fact, our relationship with Amazon, Microsoft, and Google are relationships where they know sometimes our software will recommend an outcome that they can't monetize but they still choose to work with us and they still choose to recommend us and in some cases, leverage us for their clients to make sure their clients are getting the best value for their spent. >> Well, Brian Kelly, Charlotte North Carolina based CLoudGenera. Appreciate you joining. Thanks so much for sharing with us some of the nuance and complexity that you're trying to help enterprises glean through. We'll be back. Check out lots more coverage at theCUBE.net. So many shows where companies are trying to sort through this very complicated space. So be sure to check out theCUBE.net for all the videos. Wikibon.com where we're digging through with our analysis on our team. I'm Stu Miniman, thanks so much for watching theCUBE. (upbeat music)

>> Announcer: Live from Las Vegas, it's The Cube. Covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to The Cube's continuing coverage of AWS re:Invent 2017. We're live from Las Vegas, day three. There's still a ton of people here. We have a great guest next and we're excited to talk about Mark Kelly, the director of Cloud and Infrastructure Services Architecture, talking with myself, Lisa Martin, and my co-host Stu Miniman. Mark, welcome to The Cube. >> Thank you, glad to be here. >> So Scripps Networks, tell us a little bit about that. I know a few things, HGTV, Food Network, I watch those a lot but, tell us a little bit more about Scripps Network. >> So Scripps, when I say that name, most people do not know it. But we are the leading provider of home, food, and travel content for broadcast, the web, and for emerging technologies at this point in time. So, we've got a lot of brands in our umbrella. You said HGTV, we've got Food Network in there, Cooking Channel, DIY Network, Great American Country, and Travel Channel. >> Yeah so Mark, I know my family binges a lot of these shows so-- >> Really? >> As do I. >> Take us little bit, you know, what's happening in that industry today? You know binging versus watching online, cloud, digital, the joke of course is that at least things are pretty stable and not changing in your world, right? >> Oh I know, absolutely. It is changing on a very rapid pace so, as more and more people, you know, the big buzzword is that cord cutting thing. We have got big concern in out industry around that. But as more and more people talk about it, we're adapting our technologies to be there just to provide for them. So we're on those emerging technologies. We're on all of the said top boxes. Apple TV, Roku, we're actually developing networks specifically for those technologies. So we're trying to adapt. The broadcast world is still our bread and butter, so until we figure out the revenue models for these new technologies, we're gonna be in the broadcast world for some time. >> So Mark, talk us through a little bit of what's your role there. You've been there six years I believe you said. How has Cloud changed the way Scripps works. >> So, Cloud has definitely changed the way we work. When I first came on board, Scripps was looking for a way to move the business faster. Scripps, because it is changing so rapidly, they're in the business of-- They have to compete with startups. And when they're competing with startups, startups don't have the same process as it controls around everything that the bigger enterprises do. So it was an extreme challenge to them. And you know, when they don't understand-- They don't have budget concerns like big enterprises either. When I go in to do a project to launch a new network, they don't understand it. I've got to buy hundreds of thousand dollars worth of hardware or whatever associated with it. So when we're looking at the Cloud, we needed a way to accelerate that. We wanted the make the business process much quicker. We weren't going to have those lead times for purchasing hardware, purchasing software, getting licensed, you know, racking it, stacking it, doing all that. We were looking to ways to move that out of the way so everybody could focus on providing more value for the business. And that was the primary reason we actually started looking at the cloud. >> So from an end user goal perspective, obviously you mentioned speed and having to compete with other networks and other native original content companies. How does the end users demand for 24 by 7 content, how does that drive really, the pace of innovation that Scripps has to meet? >> Yeah that is a very good question. I think we're still trying to figure that out because the whole consumption method for all of our end users is changing. They're going from their traditional TV to where they're watching it on their phone, to switching to their iPads, to everything else in between. So we're developing technology methods so that we're providing it for them as they need it and want it. >> Yeah, Mark can you give us a snapshot of what is your infrastructure look like today? What are the kinds of major things that have changed and what's kind of on the table? >> Today we are running about 3000 instances in AWS. So AWS is our primary cloud provider. We run a lot of auto scaling to take into account our seasonal loads. That's probably one thing that we-- One of the challenges we had going into the cloud is that we were up against certain times of the year when the load was extremely high but it was only extremely high for a couple of weeks. I mean literally we'll be running at two to three hundred percent of what normal was, and it would do it for two to three weeks. So we were having to purchase hardware in advance for that and it would just sit there idle for the rest of the year. So we were looking to ways to avoid that excess purchase and still scale to support our consumers and needs. >> So when you started this journey, and we were talking to Veeam earlier about-- Cloud is a destination, you get there, great, you're done. But when you start this journey you mentioned AWS and we're here at re:Invent, where did you start? What were some of the stakeholders that you had (Mark laughs) on the business side that you had to say, >> Absolutely. >> Alright guys, let's come to the table, we have a great opportunity here, this industry is transforming, as you know, the joke Stu made earlier. Where did you start with those business discussions? >> So I think it was more around trying to figure out that solution. It's like when I said earlier we're trying to get to market quicker. So it was easier to go to the stakeholder and say, "Hey I think I can go this route, and I think I can get you to market twice as fast." >> Lisa: Their ears perk up? >> Oh absolutely. Ears will perk up, eyes will light up. They're like, "Really? How much more is this gonna cost me?" And I'm like, I don't think we're gonna-- They went to represent the on-demand cost models. I think we don't have to do all these big upfront costs and that got a little bit more excitement out of the stakeholders. And we went forward from there. So we would um-- It took a while. Don't get me wrong. Everybody gets set in their ways. They're going to do things normally. Change sometimes is difficult to push through. >> Lisa: Absolute-- Cultural change. Very, very challenging. >> Absolutely. So it is a complete cultural change. They go from your traditional on-premise to the cloud model where you're not managing the hardware as much. You're focusing on the engineering around it. >> So Mark, you bring up managing. You know, monitoring something that's gonna change very differently. Talk a little bit about your people, you know, the skill sets they had to change, what's the difference is kind of before, during, and after that migration. >> So beforehand, when we were on our on premise environment, we were focused on tool sets, for monitoring, and managing infrastructure that were very vast. I mean we had a large number of them. One of our goals moving to the cloud was to consolidate that tool so that we wanted to get down to a minimal set that would actually accomplish our goals to get everything that we needed. So we didn't have to go through training people to learn 50 different tool sets for monitoring whatever it was. Network equipment, storage equipment, or the computer equipment. We were actually focusing on monitoring our applications and still getting some of that underlying infrastructure reporting on our monitoring, but we didn't have to have the same level where we were monitoring the hypervisors, we were monitoring the network switches, that kind of went away. So our focus became more on the operating system up and engineers developed. They no longer had to focus on that hardware. >> So what are you using for that, you know, how many people does it take to do that? Do you know if it can kind of compare to what you had before, yeah. >> Our standard monitoring switch is actually composed of New Relic. New Relic has been a great partner for us. They had the same mindset as us. We're looking to compete with the startups, at the time New Relic was the startup. Because we've been using them for between five and six years now. We brought them in because they had that same hunger and mentality that we were looking for. Their culture mashed really well. And we got in and deployed all of their suites to every environment. We actually leverage it in from development up through production. So we try not to separate our monitoring. We try to keep it all uniform so out troubleshooting gets a lot simpler. We actually have the same people monitoring our DeckStats that are monitoring out production stats. So they can troubleshoot and help get through there. It became a lot easier for them to do that. >> Could you talk about kind of, how many people you had, managing infrastructure before versus the monitoring, and some of the training they had to go through or? >> Before, it was all specialized people. I don't even have that. I couldn't even give you the headcount cause most of that was before my time. >> Stu: Yeah. >> But every individual was actually specialized on each application for monitoring. So it was actually teams that would focus on each part of the business. So as we migrated into cloud, we became more standardized. Made it simpler. We actually have our-- My cloud team is really in between about 15 to 20 people. And we're managing 3000 instances in AWS, and about six petabytes of storage. We've got quite a bit of a content up there already. >> And you're on the customer advisory board for New Relic. >> Mark: I am. >> You mentioned cultural alignment between Scripps and that vendor, and that's really key, but talk to us about this collaboration and it sounds-- Maybe by direction of that, you're able to maybe influence some of the things and help them make their technologies better. >> Absolutely, we've got a really good relationship with them so anytime we have a challenge, one of our current challenges is serverless. As we move, we have a lot of development teams that want to move into serverless. We've been working with the New Relic teams and giving feedback to them on what our challenges are with that, and how we're monitoring it, cause we've got certain things where I wanna be able to monitor those functions in serverless, and I'll need to give a cost back to my stakeholders to say this is what you'd cost. It's challenging to do that now but we're working with the New Relic team to help them deliver some of that knowledge to us. >> Mark, you hit a hot button for me. So bring us inside, you know, why serverless, and what are you hoping to gain from that. I've seen New Relic actually has been tracking for the last couple of years, adoption of containers in serverless so-- >> Containers in serverless is kind of the new hotness you know. We've been moving into serverless primarily because again, it's the next generation of speed for us. Makes it even simpler for the developers to get started, we can give them a standard framework, they can start developing their code and just push deploy and it's running, and they don't have to worry about any infrastructure or managing anything. Again, the challenge has been the monitoring part of it, but working through that and actually getting pretty good results out of it so far. >> So you've got about 70% of your consumer facing side is on AWS which has got some latency sensitive workloads that are still on-prem? >> A hundred percent of my consumer facing properties are on AWS. >> Oh fantastic. >> We do have some workloads that-- Those are really not designed for cloud. It's our end use, end financial systems, our critical business systems that need to be close to those departments. Those actually still live on-premise for us. When we started this journey, the on-premise was-- it was a slow, horrible process but, as we evolved, the cloud, they've evolved that on-premise stuff to keep us with them as well. We're actually looking at, so you know, some of the other monitoring solutions out there. New Relic has been an option for us to actually look at on-premise will, monitoring as well. >> So all the advancements that you guys have achieved in your six year or so transition to cloud that you've talked about. What's next for Scripps? What are some of the maybe new business opportunities that this optimization, cost reduction is enabling? >> So next for us is actually machine learning and AI. We have large initiatives going on that right now. We are trying to analyze our video, analyze our content, lots of it's to help remove some of the manual processes that we have now. Because a lot of that stuff when you're delivering to our different partners, there's certain requirements around the video, and the only way to do it right now is with eyeballs watching the videos. So is this somebody sitting there watching it for hours and hours a day. We're leveraging the machine learning stuff to actually auto classify this video, pull out thumbnails for the authors so they can put it in there, the metadata awareness form, and we're doing lots of things with AI. So we're looking for that to be a really hot feature for us in the next couple of years. >> Excited with what you heard this week from AWS about AI in ML? >> Absolutely. The first day keynotes were completely blown away. They were all things we were looking for. >> Stu: Anything specific that you've been waiting for, or just not waiting for, but got excited by? >> Yeah there was lots of it. The Kinesis video streams were actually really good. The video API, I'm drawing a blank on the exact name of it, but that one actually had some really good features for us because we are looking to do exact things that that one does. We're looking to pull time stamps out for when stuff shows up in videos and provide that back to our end users where they can search and find things in the videos much more quickly. >> Excellent. Well Mark, thanks so much for stopping by The Cube and sharing what you guys have been doing at Scripps Network with us. >> Mark: No problem. >> It sounds like you've seen a massive transition and you're really have a great foundation to continue going forward and >> Thank you. >> Lisa: And we look forward to continue to watch great shows on the network. >> Awesome, thank you guys. >> And for my co-host Stu Miniman, I'm Lisa Martin. We would like to thank Mark for stopping by. You're watching The Cube's continuing coverage from Las Vegas of AWS re:Invent 2017. Stick around guys, we'll be right back.

>> Narrator: Live from Las Vegas, it's The Cube, covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Bob: It's actually a little quieter here. >> Hey, welcome back to AWS re:Invent 2017. I am Lisa Martin. We're all very chatty. You can hear a lot of chatty folks behind us. This is day two of our continuing coverage. 42,000 people here, amazing. I'm Lisa Martin with my co-host Keith Townsend, and we're very excited to be joined by a Cube alumni Bob Muglia, CEO and President of Snowflake. >> Thank you. >> Lisa: Welcome back. >> Thank you, good to be back. >> And Kelly Mungary, the Director of Enterprise Data and Analytics from Lionsgate. A great use case from Snowflake. Thanks so much guys for joining us. So one of the hot things going on today at the event is your announcement Bob with AWS and Snowpipe. What is Snowpipe? How do customers get started with it? >> Great, well thanks. We're excited about Snowpipe. Snowpipe is a way of ingesting data into Snowflake in a streaming, continuous way. You simply can drop new data that's coming in into S3 and we'll ingest it for you automatically. Makes that super, super simple. Brings the data in continuously into your data warehouse, ensuring that you're always up to date and your analysts are getting the latest insights and the latest data. >> So, when you guys were founded, about five years ago, as the marketing says on your website, a complete data warehouse built for the Cloud. What was the opportunity back then? What did you see that was missing, and how has Snowflake evolved to really be a leader in this space? >> So you know, if you go back five years this was a time frame where no SQL was the big rage, and everybody was talking about how SQL was passe and it's something that you're not see in the future. Our founders had a different view, they had been working on true relational databases for almost 20 years, and they recognized the power of SQL and relational technology but they also saw that customers were experiencing significant limits with existing technology, and those limits really restricted what people could do. They saw in the Cloud and what Amazon had done the ability to build a all new database that takes advantage of the full elasticity and power of the Cloud to deliver whatever set of analytics capabilities that the business requires. However much data you want, however many queries simultaneously. Snowflake takes what you love about a relational database and removes all the limits, and allows you to operate in a very different way. And our founders had that vision five years ago, and really successfully executed on it. The product has worked beyond our dreams, and our customers, our response from our customers is what we get so excited about. >> So, the saying is "Data is the new oil". However, just as oil is really hard to drill for and find, finding the data to service up, to even put in a data lake to analyze has been a challenge. How did you guys go about identifying what data should even be streamed to Snowpipe? >> Well, yeah, that's a great question. I mean, in entertainment today, we're experiencing probably like in pretty much every type of business. A data explosion. We have, you know, streaming is big now. We have subscription data coming in, billing data, social media data, and on and on. And the thing is, it's not coming in a normal, regular format. It's coming in what we call a semi-structured, structured, json, xml. So, up until Snowflake came onto the scene with a truly Cloud based SAAS solution for data warehousing pretty much everyone was struggling to wrangle in all these data sets. Snowpipe is a great example of one of the avenues of bringing in these multiple data sets, merging them real time, and getting the analytics out to your business in an agile way that has never been seen before. >> So, can you talk a little bit about that experience? Kinda that day one up, you were taking these separate data sources, whether it's ERP solution, data from original content, merging that together and then being able to analyze that. What was that day one experience like? >> Well, you know, I gotta tell you, it evolves around a word, that word is "Yes", okay? And data architects and executives and leaders within pretty much every company are used to saying, "We'll get to that" and "We'll put it on the road map", "We could do that six months out", "Three months out". So what happened when I implemented Snowflake was I was just walking into meetings and going, "Yes". "You got it". "No worries, let's do it". >> Lisa: It liberated. >> Well, it's changes, it's not only liberating, it changes the individual's opportunities, the team's opportunities, the company's opportunities, and ultimately, revenue. So, I think it's just an amazing new way of approaching data warehousing. >> So Bob, can you talk a little bit about the partnership with AWS, and the power to bring that type of capability to customers? Data lakes are really hard to do that type of thing run a query against to get instant answers. Talk about the partnership with AWS to bring that type of capability. >> Well Amazon's been a fantastic partner of ours, and we really enjoy working with Amazon. We wind up working together with them to solve customer problems. Which is what I think is so fantastic. And with Snowflake, on top of Amazon, you can do what Kelly's saying. You can say yes, because all of a sudden you can now bring all of your data together in one place. Technology has limited, it's technology that has caused data to be in disparate silos. People don't want their data all scattered all over the place. It's all in these different places because limits to technology force people to do that. With the Cloud, and with what Amazon has done and with a product like Snowflake, you can bring all of that data together, and the thing that's interesting, where Kelly is going, is it can change the culture of a company, and the way people work. All of a sudden, data is not power. Data is available to everyone, and it's democratizing. Every person can work with data and help to bring the business forward. And it can really change the dynamics about the way people work. >> And Kelly, you just spoke at the multi-city Cloud Analytics Tour that Snowflake just did. You spoke in Santa Monica, one of my favorite places. You talked about a data driven culture. And we hear data driven in so many different conversations, but how did you actually go about facilitating a data driven culture. Who are some of the early adopters, and what business problems have you been able to solve by saying yes? >> Well, I can speak entertainment in general. I think that it's all about technology it's about talent, and it's about teaching. And with technology being the core of that. If we go back five years, six years, seven years, it was really hard to walk into a room, have an idea, a concept, around social media, around streaming data, around billing, around accounting. And to have an agile approach that you could bring together within a week or so forth. So what's happening is, now that we've implemented Snowflake on AWS and some of the other what I call dream tools on top of that. The dream stack, which includes Snowflake. It's more about integrating with the business. Now we can speak the same language with them. Now we can walk into a room and they're glad to see me now. And at the end of the day, it's new, it's all new. So, this is something that I say sometimes, in kidding, but it's actually true. It's as if Snowflake had a time traveler on staff that went forward in the future ten years to determine how things should be done in the big data space, and then came back and developed it. And that's how futuristic they are, but proven at the same time. And that allows us to cultivate that data driven culture within entertainment, because we have tools and we have the agile approach that the business is looking for. >> So, Kelly, I'm really interested, and I love the concept of making data available to everyone. That's been a theme of this conference from the keynote this morning, which is putting tools in builder's hands, and allowing builders to do what they do. >> Kelly: That's right. >> And we're always surprised at what users come back with. What's one of the biggest surprises from the use cases, now that you've enabled your users. >> Well, I'm gonna give you one that's based on AWS and Snowflake. A catch phrase you hear a lot of is "Data center of excellence", and a lot of us are trying to build out these data centers of excellence, but it's a little bit of an oxymoron to the fact that a data center of excellence is really about enabling your business and finding champions within marketing, within sales, within accounting, and giving them the ability to have self-service business intelligence, self-service data warehousing. The kinds of things that, again, we go back five, six years ago, you couldn't even have that conversation. I'll tell you today, I can walk into a room, and say, "Okay, who here is interested in learning "about data warehousing?". And there'll be somebody, "Okay, great". Within an hour, I'll have you being dangerous in terms of setting up, standing up, configuring and loading a data warehouse. That's unheard of, and it's all due to Snowflake and their new technology. >> I'd love to understand Bob, from your perspective. First of all, it sounds like you have a crystal ball according to Kelly, which is awesome. But second of all, collaboration, we talked about that earlier. Andy Jassy is very well known and very vocal about visiting customers every week. And I love their bottom, their backwards approach to, before building a product, to try to say, "What problem can we solve?". They're actually working with customers first. What are their requirements? Tell me a little bit Bob about the collaboration that Snowflake has with Lionsgate, or other customers. How are they helping to influence your crystal ball? >> You know what, this is where I think what Amazon has done, and Andy has done a fantastic job. There's so much to learn from them, and the customer centricity that Amazon has always had is something that we have really focused to bring into Snowflake, and really build deeply into our culture. I've sort of said many, many times, Snowflake is a value space company. Our values are important to us, they're prominent in our website. Our first value is we put our customer's first. What I'm most proud of is, every customer who has focused on deploying Snowflake, has successfully deployed Snowflake, and we learn from them. We engage with them. We partner with them. All of our customers are our partners. Kelly and Lionsgate are examples of customers that we learn from every day, and it's such a rewarding thing to hear what they want to do. You look at Snowpipe and what Snowpipe is, that came from customers, we learned that from customers. You look at so many features, so many details. It's iterative learning with customers. And what's interesting about that, it's listening to customers, but it's also understanding what they do. One of the things that's interesting about Snowflake is is that as a company we run Snowflake on Snowflake. All of our data is in Snowflake. All of our sales data, our financial data, our marketing data, our product support data, our engineering data. Every time a user runs a query, that query is logged in Snowflake and intrinsics about it are logged. So what's interesting is because it's all in one place, and it's all accessible, we can answer essentially any question, about what's been done. And then, driving the culture to do that is an important thing. One of the things I do find interesting is, even at Snowflake, even at this data centered company, even where everything is all centralized, I still find sometimes people don't reference it. And I'm constantly reinforcing that your intuition, you know, you're really smart, you're really intuitive, but you could be wrong. And if you can answer the question based on what's happened, what your customers are doing, because it's in the data, and you can get that answer quickly, it's a totally different world. And that's what you can do when you have a tool with the power of what Snowflake can deliver, is you could answer effectively any business question in just a matter of minutes, and that's transformative, it's transformative to the way people work, and that, to me, that's about what it means to build a data driven culture. Is to reinforce that the answer is inside what customers are doing. And so often, that is encapsulated in the data. >> Wow, your energy is incredible. We thank you so much Bob and Kelly for coming on and sharing your story. And I think a lot of our viewers are gonna learn some great lessons from both of you on collaboration on transformations. So thanks so much for stopping by. >> Yeah. >> Thank you so much, we really enjoyed it. Thanks a lot. >> Likewise, great to meet you. >> Thanks Kelly. >> Thank you. >> For my co-host Keith Townsend, and for Kelly and Bob, I am Lisa Martin. You've been watching The Cube, live on day two, continuing coverage at AWS re:Invent 2017. Stick around, we have great more guests coming up. (upbeat music)

>>Live from Seattle, Washington. It's the queue at Tableau conference 2014 brought to you by headline sponsor Tableau.. >>Here are your hosts, John furrier and Jeff Kelly. >>Okay, welcome back. And when we hear live in Seattle, Washington for the cube, this is our flagship program. We go out to the events, expect to see with the noise. I'm John furrier, my coach Jeff Kelly, analysts that we bond.org and we'd love to go talk to the senior leaders of the companies that are hosting the event, the Tablo data 14 conference and Kelly, right EVP of sales for Tableau software. Welcome to the cube. >>Thank you. Thank you for having me. >>So, uh, you're under the, you're in the pressure cooker seat. So sales is everything, right? You know, you guys are a public company and you have to perform. Performance is happy customers, they pay you money, you collect the cash, you put it in the bank and invested into your business and do it again and again. Um, you've done very well as a company. You guys have been great. So I got to ask you, um, about where Chad blow is today. Share with the folks a little bit of the history. Um, you know, we've been big fans of the company actually. We are, uh, you know, me personally being an entrepreneur, I love when companies get built by the founders and don't have to raise money to start the company. They get critical mass and take the extra growth capital. And you guys have done that. You've been in real big success story is an entrepreneurial venture. So share the culture and kind of where you guys are now and with the customer base, the culture. >>Oh, that's a lot of questions all in one. Uh, well thank you for having me. It's a pleasure being here. You know, you asked about what it's been like on this whole journey and a lot of the people that were here at the beginning, we're all still here, right? So I was the first salesperson at Tableau. I joined a month before we started version one. And I've seen how things have changed and evolved. And the truth of the matter is we have a lot more people. We have more customers, but the culture of the company has stayed really sound from the beginning. We were a bunch of people who were very, very passionate about this mission to help people see and understand data. And that's still our mission today. So from the day I started to now, it's all been focused on empowering people to answer their questions more. And so the culture of the people that started were very passionate, really excited about the mission, really a group of company builders who wanted to roll up their sleeves and go make things happen. And yes, we're a bigger company now. Now we're a public company, but we're still just barely, barely scratching the surface. I mean, they're 55 million companies out there in the world. We have 20,000 customers. So we have a long, long way to go. >>I love that you're a senior lead as a company. You've been there as the first is awesome. So I've got to ask you, I mean there's always a moment in time where you go, Oh, will we make it? Or that moment where you going? We've the flywheels going. Could you share just some color around because startups are very hard. Think they're easy all yet. Anyone can do that. So share with a moment where you go, Oh my God, it's gonna be tough shipping where they're shipping a product or hiring or personnel or, and an aha moment where you said, Oh my God, we're doing it. Well, >>when, when you're in this company building mode, it's just you put your head down and you go and you're just go, go, go. And it's always about going and finding the next customer, making sure that customer is excited, ecstatic, hiring more people on the team, making sure that culture is still vibing. And we really just took the focus of doing things one day at a time and treating each customer like their goals. And that's still what we do. Our customers are our lifeblood, right? And that's what's keeping us going. So there were certain times at during during the whole journey, I mean, I remember 2009 when the economy was slowing down. Tableau actually still grew at a really healthy clip, but it was harder. But there was really no time that I felt, Oh, this is a huge uphill battle. I, it was an uphill battle all the time. >>We're still kind of the underdogs, right, where there's tons of customers to help. We haven't helped tons of them yet. And it's just doing things to make sure that we're building good products, empowering people to you go, wow, we're really doing this well. Did you take a break and pause and say, Hey, we're doing it, we're making it. Well, you know, I think one of the moments that really resonated for me is we worked so long to say is Tao, is Tablo gonna make it just keep doing what we're doing and believe in what we're doing. Believe in that mission. And for a long time it was, can we make it to be a public company? Can we ever get to that moment? And I remember the day, it was May 17th last year, 2013 when we were on the floor of the New York stock exchange. And we had brought tons of customers. I mean not customers. We had a lot of employees. So we had over a hundred employees filling out the floor. And in that moment when we had the management team and Christian was ringing the bell, just looking out at all these people who had helped us build Tableau and get to that day. I think that was a moment of real. A lot of pride. And it's funny talking about it right now because where I just came from is gesturing in the bell again at the, at the closing bell. So >>cause that's a lot of those steps are very hard. I mean Jeff and I talked to special all the time. We'll get a big pile of money from the VCs. Four or five guys. >>Well we didn't get a big pile of, >>I know, I just, why I was thinking why it's such a great story because the pilot money could complicate it. Being hungry actually is motivating. So, and then having that customer product successes is a great testimony. So we, I mean I think you guys are a great testimonial to successful startups. Thank you. So let's dig into the sales strategy a little bit. So as you've grown up Tableau, when you started off you really, this is you know, this very nimble underdog. You were kind of going in there with really disrupting the old guard BI players. A lot of, more of a kind of I think a desktop focus, a single user kind of focus. You've expanded, you've got enterprise licenses, now you've got cloud, now you've got mobile. How has the sales strategy evolved over that time period to, to adopt or to adjust to these new, uh, Kevin, the new ways of reaching your customer? >>Well, you know, our model is actually really quite simple. I'll go back to what I had talked about before. We help people see and understand data. So everything about what we're trying to do is to help people to be able to answer their own questions and to empower them with flexibility and agility and self service. And as we add additional products, it's really just extending the number of people that we can help. Some people want to work in the cloud, so Tableau online's better. Some people want to do it on their desktop so they're doing it more with tablet, desktop, some people out in the server and so as long as our salespeople are are looking for what is the best way that I can help this customer to be able to be more self sufficient in answering their own question and then we really hear what's the customer's use case. >>Then to answer that we have different products that actually fit that in. So in terms of how our sales strategy is working, the sales strategy is the same as it always is so we don't really focus on what to do with this product line versus that product line or this product line or small customers versus big customers. It's really all in this landed expand, let the customer buy as big or as little as they want to get started. We'll work with them very closely to make them successful and then as they're successful, they'll come back to buy more. And we have all these different ways that they can buy software and types of software that they can buy to be able to address their needs of self service agility and answering their own questions. >>The buyer, the profile of the buyer changed at all. So I know obviously Tableau is all about the end user, the person who's interacting with the software interact with the data as you'd like to focus on. But as you move to larger accounts, larger enterprises, are you still dealing directly with that user when you sell? Are you dealing with essential it more often? Right, right. >>And I guess that was kind of my question. You evolve to that, you know, I think that's a great, it's a great question because if I were to roll back the clock to almost 10 years ago when I was starting, we were, we were actually interacting mostly with the business user. So the end user and over time we're interacting with the C level, the C suite, we're interacting with the VP of it, we're interacting with the business users. And actually we're, we're working with both groups a lot. So what happened early on was we'd start with the business and over time as they bought more and more and more, they would bring us into it. And now actually we're seeing a shift that sometimes it's the it and the C suite that's coming to us and they're saying, Hey, we want to be able to empower our user community answered their own questions, but we need to be able to do that in a more secure governed control type of way. >>And is there a way that we can balance with Tableau? So we see it happening in both. I think one of the interesting changes that we're seeing is there is a cultural shift that's going on right now and companies are now starting to realize that the way that the past is very different than the wave of the future. So the wave of the past was if you had a question, you threw it over the fence to this central group that was report writers and these report writers knew how to code and they were very, very specialized. And the user that had the question, they had absolutely no idea how to operate those systems well. Now that companies are saying as data's coming in at such a fast clip, it just takes too long. They have to empower people to be able to answer their own questions, otherwise they end up being at a standstill. And so as we start having more discussions with the enterprise in the C suite, those folks who are in it and the CIO who realize, Hey, there's a shift that's going on and we need to be doing things in the way of where the world is going, not the way that we've done it in the past. It makes that conversation quite a bit easier. And so now we're seeing more and more conversations that are along those lines of how are we going to keep our organization to be competitive going into the. >>So I've got to ask you about the international expansion. We were talking earlier with your colleague Dave Martin, um, and also move at the HP big data event. And I had also had a conversation with Dave, CEO firearm, huge international. He says, John, my big growth happened. He's public company. You got you guys, he says international huge growth opportunity for us. So you have a Tam, then you have 55 million customers. You have one of those unique products at all customers need. So that's good. Check growth is on the horizon. How are you going to attack that new territory? I mean international and to grow, I mean channel strategy, indirect big part of it. I mean you guys are enabling people to create value. That seems to be the formula for a great indirect strategy. You've built a successful direct sales force graduations, but that's can take time. >>Yeah. Well you know, our model for international international is a huge opportunity for us. So we are putting a lot of resources and time into expanding internationally. We have our headquarters over in AMEA, we have headquarters over an APAC. We're now just w we opened up offices in Japan and in Germany we opened up operations in India. We are opening up another, a bigger office in, in Australia and even in Latin America, Brazil and Mexico. There's a fair amount going on now as we're going to market. It actually is pretty similar, so we're building direct sales force in all of those regions. But international, as you start doing more international, the channel becomes even increasingly important and it is, we're focusing a lot of time and energy on the channel here in the States. But in places like AMEA and certain locations over an APAC and and certainly in Latin America there is just the way of doing business tends to be more around the channel. >>Equalization has always been a nice thing of having in country operations. So that's always been kind of the international playbook. But with data I can be complicated. So having people in country, in a channel delivering value, is that the preferred way you guys, is that what you're saying? Is that, is that kind of? >>You know what I th th well the interesting part about Tableau is as we talked about, it's agnostic. Anyone can use it. And so when we go into a new country, there's two ways that we can go in. We can go on with our directing and we can go in with empowering our channel. And we actually have customers in over a hundred countries throughout the world, right? And we have partners operating in a large number of those. So our partners often are the ones that are the local feet on the street. They're going and they're having the conversations and, and they're providing the local support in the language and in the culture that it is now. When we actually open up offices in those different regions, we try to be very aligned, not only just putting our salespeople in, but having our entire company all lined up behind it. So we have our sales team, we have our marketing, we have our product. So when we go into Japan, for instance, we want to be able to have the website in Japanese. We want to be able to have the product localized in Japanese, we want to be able to have support staff that can help. And, and then of course having the partner ecosystem where the partners are able to help us make those customers all realistic. >>Flip yet in the U S I mean, as you guys get the channel going, has there been some channel conflict on order orders and who owns the accounts? >>Yeah, well you know what, our channel, we were developing a lot in the channel, but we're still pretty early in the, in our channel development and we're spending a lot of time to make sure that our channel is really successful as well as our, as well as our customers being successful. And the truth of the matter is we can't, we can't go and help all the people that we want to help without embracing the channel. And they're system integrators that they're in there and they're doing huge multi-year projects and we're working closely with them. And when we talk about the channel, we're working with resellers but also OEM and technology partners and system integrators. So lots and lots of channel activity going on. >>Yeah, I think you just touched on, well I think is one of the going to be one of the challenges for Tableau is that you can't, as you expand so fast, you can't keep your finger or your pulse on the customer quite as quite as closely as maybe you'd like. You've got to, you've got to count on the channel to do some of that. So that, and Tableau is of course known for being very customer focused. I mean the show here, you know, the crowds are cheering and Christian as he's giving his keynote and different visualizations are being demoed on stage and the crowds standing on their feet, you know, to keep that kind of customer focus as you expand. I think it's a challenge. It sounds like you really got to focus on those relationships with your partners and your OEM partners, et cetera. So they kind of understand that the Tableau approach is that, yeah, >>I I, I totally agree. Actually. I think you can even see at the show today, if you go down to that partner expo hall, there are so many partners, you're way more partners than we've ever had before. And when I was checking in with them, even yesterday where the show hadn't even started, they're getting a huge number of leads that are coming in and they're, there's so many opportunities for us to work together with our partners. In fact, this year, not only did we build of being really growing our partner sales team, but we had a whole series of partner summits this year and we traveled around the world. We had one in AMEA, one in APAC, one here in the States of being able to really train and enable our partners not only how to sell Tableau, but to work with them in a conversation of what's the best way that we can engage with them and make them really successful. So when we think about our ecosystem, it's not just about our customers, it's now about our customers and about our partners. And we're all part of the Tableau >>here. So obviously one of the things that you guys have done, you do a great job because you're such walking testimonials as customers. Um, what channel partners do you have as customers and that are top references now that you're showcasing and what end users are you showcasing here at this event? Can you name names and? >>Yeah, well I think you can, you can actually go downstairs and look in the partners of who we are and we're doing Watson, lots of, uh, partner with, with whether it's Vertica or with Alteryx or with data, uh, where we're doing joint sales and a lot of those, a lot of the that you'll see here, they're using Tableau internally in a pretty big way. And then in terms of customers, and we have showcases all over the place. I think we have a hundred customer speakers that are here. So there are there hospitals, we have Barnes, Jewish and Seattle children's who are talking about how they're using Tableau actually in the operating rooms and with nurses. And to be able to help save lives. We have education institutions who are using Tableau for how they can teach better in school, how the teachers can have their administration going. Uh, and we also have a number of corporate customers who are helping with that as well. >>So one of the things that we always talk about when we talk about startups, you guys want to start certainly, but company building is a great team. You guys are on that next generation of building out. Um, you always get the question, um, high touch sales, indirect low cost, our automated self-service if you're, you know, kind of a platform, um, inside sales is a great strategy for expanding out growth. Um, but it's hard. Um, do you guys have an inside sales organization? You, are you building it out? Is that a big part of your increase in your customer service? Cause a lot of you got great fans. Loyalties, high products is good. So are you building out? >>Yeah. You know, we actually, we got predominantly with inside sales, so we started with inside sales and then enterprise sales came later. And with our inside sales, we still have a very, very robust inside sales. We have kind of both models, some customers prefer to be interacted with field, face to face. And so we have field folks that are all over, uh, in our, all our major regions and we have a lot of inside folks. And the same is true when we look at how we're going to support them. So we have technical folks and services folks in training folks that will go out and meet the customer on their site, help to enable them setting up center of excellence, all that. And then we have a large number of that is that is done remotely. The benefit we have at Tableau is actually tablets, pretty easy to use. >>And so we don't always have to sit down and do it beside them. So how about sales compensation, if you will? Not with numbers, but like, I mean culturally is it, is it, we're hiring you killed like in the early days of Cisco sales guys were making zillions of dollars. Um, there's Tableau have, um, the kind of product pricing mix where you guys have a lot of like huge compensation, uh, rewards. So how does that work? You know, what we focus on having our salespeople be really excited about working here, having it be a very good as you know, right. I mean, compensation drives behavior. How do you guys, we have a lot of salespeople that have been here for a very long period of time. So we have a huge opportunity and we focus on the opportunity to help more customers and then the opportunity to have a really good career progression path. >>You know? Yes. I'm not going to answer your question, but you can keep on top a little bit about the competitive landscape. So, and again, maybe you know, because you've been with Tableau since the beginning, how has it evolved again, when you guys started, you were very much the disruptor going in. Yeah. Let's name some names, the disruptor, SAP business objects. You had Cognos, Hyperion, you guys are going in there and say, no, that's the old way. This is the new way. Um, since then you've now that some of those old players are started, they're focusing now on you know, being very self service, kind of emulating a lot of the things top load yet now you've got also kind of even newer companies, newer startups out there that are coming, even some are maybe mobile focused or cloud focused. What's the competitive landscape look like for you and from a sales perspective, again, how do you adapt as you got to come in from, you know, from the, from the new guys, you've got to come in from the old guard, you guys are targeted. >>When you're this successful you're always going to be a target. What it's like from your perspective. You know what, one of the things that we actually really focused on at Tableau, cause we talk about this a lot internally with our team is we can only control what we can control. We can control what our products are, we can control what our customer success is, we can control how we engage with our customers. And so we spend a lot of time just focusing on what it is that Tableau can do. And as we're now talking more about data discovery and agile and analytics and self-service, there's a lot of noise out there. A lot of other players who are saying that they can do the same thing and that they can do it as well. And our strategy is really, if you think you can use that, so why don't you go download their product and download our product and see how long it takes. And we actually encourage people to go out and test it out and try. And what we find is when someone is really interested in self service and helping people to answer their own questions, then the answer to them becomes really clear when it is an a question of we just want traditional old pixel perfect reporting you have. There are a lot of people that can play in that game. Uh, but we're finding the conversations changing quite a bit when they really want self-service. Then we actually feel like we're, we're pretty well positioned competitively. >>So are your lottery, your deals going up in, you know, competitive environments where you've got Tableau lined up against business objects against, I don't know. Good data against whoever. Is it a lot of that or do you have a lot of, you know, people who are trying the product love it and just say, Hey, we want to go with Tableau. >>You know, there's both, but the majority of our deals are actually when we're competing against the status quo, they actually aren't even looking at other business intelligence. They might have it in their company but it's not solving their need and their requirement. So a lot of people are just using what is already commissioned on their computer. Now there are situations where there is a competitive bake-off and we love competition. I mess with salespeople. Do we go and compete? Uh, but we're finding that the conversation is shifting and where we tend to really focus our time and energy is with those companies that are really looking for the new way. >>Kelly, you got to get the, I got to get the hook here, but I want to ask you two final questions. One is an easy one. What's it like working with Christian? >>It's great working with Christen. You know what? We've worked together all for so long and it's, it's really, we say it's like we're a family, right? We, we know each other, we know each other's families, we know each other's kids and it's pretty much the same as it was when I started almost 10 years ago. Nothing's really >>the second question. Share with the folks out there watching what is the culture of Tablo, if you could. Every culture has their own little weird tweak that makes them so unique. Intel, it's Moore's law. What's Tableau's cultural? >>Well, you have to go ask all the Tablo people if they think our culture is weird, probably not like a unique tweak that makes them so successful. The Moore's law was first called the weird, you know, people that work here are really, really passionate about what we do. We're passionate, we're mission focus and people have a lot of fun at what they do. They work hard and they play hard and it's, it's a very fun place to be. But we go fast. Yeah, certainly not weird, that's for sure. I didn't mean that, but I want a good way, a good thing. And it's usually the, it's the ones that the best deals are the ones that no one sees that doesn't look like it's going to be. And you guys were certainly a great winner of our hiring, so everyone in the world were hiring. We couldn't get the sales comp out of her, but we, you know, we tried our best, uh, Kelly, seriously, thanks for coming on cue. Really appreciate it. We know the journey you've been on has fantastic. It's a >>whirlwind now. You just got to go to the next leg of the journey, which is build a global 50 million customer business. Congratulations. Thank you for having me. We'll be right back with our next guest after this short break live in Seattle, Washington to the cube. Thank you.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, This is "Breaking Analysis with Dave Vellante". >> Black Hat 22 was held in Las Vegas last week, the same time as theCUBE Supercloud event. Unlike AWS re:Inforce where words are carefully chosen to put a positive spin on security, Black Hat exposes all the warts of cyber and openly discusses its hard truths. It's a conference that's attended by technical experts who proudly share some of the vulnerabilities they've discovered, and, of course, by numerous vendors marketing their products and services. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis", we summarize what we learned from discussions with several people who attended Black Hat and our analysis from reviewing dozens of keynotes, articles, sessions, and data from a recent Black Hat Attendees Survey conducted by Black Hat and Informa, and we'll end with the discussion of what it all means for the challenges around securing the supercloud. Now, I personally did not attend, but as I said at the top, we reviewed a lot of content from the event which is renowned for its hundreds of sessions, breakouts, and strong technical content that is, as they say, unvarnished. Chris Krebs, the former director of Us cybersecurity and infrastructure security agency, CISA, he gave the keynote, and he spoke about the increasing complexity of tech stacks and the ripple effects that that has on organizational risk. Risk was a big theme at the event. Where re:Inforce tends to emphasize, again, the positive state of cybersecurity, it could be said that Black Hat, as the name implies, focuses on the other end of the spectrum. Risk, as a major theme of the event at the show, got a lot of attention. Now, there was a lot of talk, as always, about the expanded threat service, you hear that at any event that's focused on cybersecurity, and tons of emphasis on supply chain risk as a relatively new threat that's come to the CISO's minds. Now, there was also plenty of discussion about hybrid work and how remote work has dramatically increased business risk. According to data from in Intel 471's Mark Arena, the previously mentioned Black Hat Attendee Survey showed that compromise credentials posed the number one source of risk followed by infrastructure vulnerabilities and supply chain risks, so a couple of surveys here that we're citing, and we'll come back to that in a moment. At an MIT cybersecurity conference earlier last decade, theCUBE had a hypothetical conversation with former Boston Globe war correspondent, Charles Sennott, about the future of war and the role of cyber. We had similar discussions with Dr. Robert Gates on theCUBE at a ServiceNow event in 2016. At Black Hat, these discussions went well beyond the theoretical with actual data from the war in Ukraine. It's clear that modern wars are and will be supported by cyber, but the takeaways are that they will be highly situational, targeted, and unpredictable because in combat scenarios, anything can happen. People aren't necessarily at their keyboards. Now, the role of AI was certainly discussed as it is at every conference, and particularly cyber conferences. You know, it was somewhat dissed as over hyped, not surprisingly, but while AI is not a panacea to cyber exposure, automation and machine intelligence can definitely augment, what appear to be and have been stressed out, security teams can do this by recommending actions and taking other helpful types of data and presenting it in a curated form that can streamline the job of the SecOps team. Now, most cyber defenses are still going to be based on tried and true monitoring and telemetry data and log analysis and curating known signatures and analyzing consolidated data, but increasingly, AI will help with the unknowns, i.e. zero-day threats and threat actor behaviors after infiltration. Now, finally, while much lip service was given to collaboration and public-private partnerships, especially after Stuxsnet was revealed early last decade, the real truth is that threat intelligence in the private sector is still evolving. In particular, the industry, mid decade, really tried to commercially exploit proprietary intelligence and, you know, do private things like private reporting and monetize that, but attitudes toward collaboration are trending in a positive direction was one of the sort of outcomes that we heard at Black Hat. Public-private partnerships are being both mandated by government, and there seems to be a willingness to work together to fight an increasingly capable adversary. These things are definitely on the rise. Now, without this type of collaboration, securing the supercloud is going to become much more challenging and confined to narrow solutions. and we're going to talk about that little later in the segment. Okay, let's look at some of the attendees survey data from Black Hat. Just under 200 really serious security pros took the survey, so not enough to slice and dice by hair color, eye color, height, weight, and favorite movie genre, but enough to extract high level takeaways. You know, these strongly agree or disagree survey responses can sometimes give vanilla outputs, but let's look for the ones where very few respondents strongly agree or disagree with a statement or those that overwhelmingly strongly agree or somewhat agree. So it's clear from this that the respondents believe the following, one, your credentials are out there and available to criminals. Very few people thought that that was, you know, unavoidable. Second, remote work is here to stay, and third, nobody was willing to really jinx their firms and say that they strongly disagree that they'll have to respond to a major cybersecurity incident within the next 12 months. Now, as we've reported extensively, COVID has permanently changed the cybersecurity landscape and the CISO's priorities and playbook. Check out this data that queries respondents on the pandemic's impact on cybersecurity, new requirements to secure remote workers, more cloud, more threats from remote systems and remote users, and a shift away from perimeter defenses that are no longer as effective, e.g. firewall appliances. Note, however, the fifth response that's down there highlighted in green. It shows a meaningful drop in the percentage of remote workers that are disregarding corporate security policy, still too many, but 10 percentage points down from 2021 survey. Now, as we've said many times, bad user behavior will trump good security technology virtually every time. Consistent with the commentary from Mark Arena's Intel 471 threat report, fishing for credentials is the number one concern cited in the Black Hat Attendees Survey. This is a people and process problem more than a technology issue. Yes, using multifactor authentication, changing passwords, you know, using unique passwords, using password managers, et cetera, they're all great things, but if it's too hard for users to implement these things, they won't do it, they'll remain exposed, and their organizations will remain exposed. Number two in the graphic, sophisticated attacks that could expose vulnerabilities in the security infrastructure, again, consistent with the Intel 471 data, and three, supply chain risks, again, consistent with Mark Arena's commentary. Ask most CISOs their number one problem, and they'll tell you, "It's a lack of talent." That'll be on the top of their list. So it's no surprise that 63% of survey respondents believe they don't have the security staff necessary to defend against cyber threats. This speaks to the rise of managed security service providers that we've talked about previously on "Breaking Analysis". We've seen estimates that less than 50% of organizations in the US have a SOC, and we see those firms as ripe for MSSP support as well as larger firms augmenting staff with managed service providers. Now, after re:Invent, we put forth this conceptual model that discussed how the cloud was becoming the first line of defense for CISOs, and DevOps was being asked to do more, things like securing the runtime, the containers, the platform, et cetera, and audit was kind of that last line of defense. So a couple things we picked up from Black Hat which are consistent with this shift and some that are somewhat new, first, is getting visibility across the expanded threat surface was a big theme at Black Hat. This makes it even harder to identify risk, of course, this being the expanded threat surface. It's one thing to know that there's a vulnerability somewhere. It's another thing to determine the severity of the risk, but understanding how easy or difficult it is to exploit that vulnerability and how to prioritize action around that. Vulnerability is increasingly complex for CISOs as the security landscape gets complexified. So what's happening is the SOC, if there even is one at the organization, is becoming federated. No longer can there be one ivory tower that's the magic god room of data and threat detection and analysis. Rather, the SOC is becoming distributed following the data, and as we just mentioned, the SOC is being augmented by the cloud provider and the managed service providers, the MSSPs. So there's a lot of critical security data that is decentralized and this will necessitate a new cyber data model where data can be synchronized and shared across a federation of SOCs, if you will, or mini SOCs or SOC capabilities that live in and/or embedded in an organization's ecosystem. Now, to this point about cloud being the first line of defense, let's turn to a story from ETR that came out of our colleague Eric Bradley's insight in a one-on-one he did with a senior IR person at a manufacturing firm. In a piece that ETR published called "Saved by Zscaler", check out this comment. Quote, "As the last layer, we are filtering all the outgoing internet traffic through Zscaler. And when an attacker is already on your network, and they're trying to communicate with the outside to exchange encryption keys, Zscaler is already blocking the traffic. It happened to us. It happened and we were saved by Zscaler." So that's pretty cool. So not only is the cloud the first line of defense, as we sort of depicted in that previous graphic, here's an example where it's also the last line of defense. Now, let's end on what this all means to securing the supercloud. At our Supercloud 22 event last week in our Palo Alto CUBE Studios, we had a session on this topic on supercloud, securing the supercloud. Security, in our view, is going to be one of the most important and difficult challenges for the idea of supercloud to become real. We reviewed in last week's "Breaking Analysis" a detailed discussion with Snowflake co-founder and president of products, Benoit Dageville, how his company approaches security in their data cloud, what we call a superdata cloud. Snowflake doesn't use the term supercloud. They use the term datacloud, but what if you don't have the focus, the engineering depth, and the bank roll that Snowflake has? Does that mean superclouds will only be developed by those companies with deep pockets and enormous resources? Well, that's certainly possible, but on the securing the supercloud panel, we had three technical experts, Gee Rittenhouse of Skyhigh Security, Piyush Sharrma who's the founder of Accurics who sold to Tenable, and Tony Kueh, who's the former Head of Product at VMware. Now, John Furrier asked each of them, "What is missing? What's it going to take to secure the supercloud? What has to happen?" Here's what they said. Play the clip. >> This is the final question. We have one minute left. I wish we had more time. This is a great panel. We'll bring you guys back for sure after the event. What one thing needs to happen to unify or get through the other side of this fragmentation and then the challenges for supercloud? Because remember, the enterprise equation is solve complexity with more complexity. Well, that's not what the market wants. They want simplicity. They want SaaS. They want ease of use. They want infrastructure risk code. What has to happen? What do you think, each of you? >> So I can start, and extending to the previous conversation, I think we need a consortium. We need a framework that defines that if you really want to operate on supercloud, these are the 10 things that you must follow. It doesn't matter whether you take AWS, Slash, or TCP or you have all, and you will have the on-prem also, which means that it has to follow a pattern, and that pattern is what is required for supercloud, in my opinion. Otherwise, security is going everywhere. They're like they have to fix everything, find everything, and so on and so forth. It's not going to be possible. So they need a framework. They need a consortium, and this consortium needs to be, I think, needs to led by the cloud providers because they're the ones who have these foundational infrastructure elements, and the security vendor should contribute on providing more severe detections or severe findings. So that's, in my opinion, should be the model. >> Great, well, thank you, Gee. >> Yeah, I would think it's more along the lines of a business model. We've seen in cloud that the scale matters, and once you're big, you get bigger. We haven't seen that coalesce around either a vendor, a business model, or whatnot to bring all of this and connect it all together yet. So that value proposition in the industry, I think, is missing, but there's elements of it already available. >> I think there needs to be a mindset. If you look, again, history repeating itself. The internet sort of came together around set of IETF, RSC standards. Everybody embraced and extended it, right? But still, there was, at least, a baseline, and I think at that time, the largest and most innovative vendors understood that they couldn't do it by themselves, right? And so I think what we need is a mindset where these big guys, like Google, let's take an example. They're not going to win at all, but they can have a substantial share. So how do they collaborate with the ecosystem around a set of standards so that they can bring their differentiation and then embrace everybody together. >> Okay, so Gee's point about a business model is, you know, business model being missing, it's broadly true, but perhaps Snowflake serves as a business model where they've just gone out and and done it, setting or trying to set a de facto standard by which data can be shared and monetized. They're certainly setting that standard and mandating that standard within the Snowflake ecosystem with its proprietary framework. You know, perhaps that is one answer, but Tony lays out a scenario where there's a collaboration mindset around a set of standards with an ecosystem. You know, intriguing is this idea of a consortium or a framework that Piyush was talking about, and that speaks to the collaboration or lack thereof that we spoke of earlier, and his and Tony's proposal that the cloud providers should lead with the security vendor ecosystem playing a supporting role is pretty compelling, but can you see AWS and Azure and Google in a kumbaya moment getting together to make that happen? It seems unlikely, but maybe a better partnership between the US government and big tech could be a starting point. Okay, that's it for today. I want to thank the many people who attended Black Hat, reported on it, wrote about it, gave talks, did videos, and some that spoke to me that had attended the event, Becky Bracken, who is the EIC at Dark Reading. They do a phenomenal job and the entire team at Dark Reading, the news desk there, Mark Arena, whom I mentioned, Garrett O'Hara, Nash Borges, Kelly Jackson, sorry, Kelly Jackson Higgins, Roya Gordon, Robert Lipovsky, Chris Krebs, and many others, thanks for the great, great commentary and the content that you put out there, and thanks to Alex Myerson, who's on production, and Alex manages the podcasts for us. Ken Schiffman is also in our Marlborough studio as well, outside of Boston. Kristen Martin and Cheryl Knight, they help get the word out on social media and in our newsletters, and Rob Hoff is our Editor-in-Chief at SiliconANGLE and does some great editing and helps with the titles of "Breaking Analysis" quite often. Remember these episodes, they're all available as podcasts, wherever you listen, just search for "Breaking Analysis Podcasts". I publish each on wikibon.com and siliconangle.com, and you could email me, get in touch with me at david.vellante@siliconangle.com or you can DM me @dvellante or comment on my LinkedIn posts, and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis". (upbeat music)