(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

>>Hey everyone, and welcome back to The Cube's live coverage of AWS Reinvented 2022 Live from the Venetian Expo in Las Vegas. We're happy to be back. This is first full day of coverage over here last night. We've got three full days of coverage in addition to last night, and there's about 50,000 people here. This event is ready, people are ready to be back, which is so exciting. Lisa Martin here with Paul Gill and Paul, it's great to be back in person. Great to be hosting with you >>And likewise with you, Lisa. I think the first time we hosted again, >>It is our first time exactly. >>And we come here to the biggest event that the cube ever does during the year. >>It's the Super Bowl of the >>Cube. It's it's elbow to elbow out there. It's, it's, it's full tackle football, totally on the, on the floor of reinvent. And very exciting. This, you know, I've been to a lot of conferences going back 40 years, long as I can remember. Been going to tech conferences. This one, the, the intensity, the excitement around this is really unusual. People are jazzed, they're excited to be here, and that's great to see, particularly coming back from two years of isolation. >>Absolutely. The energy is so palpable. Even yesterday, evening, afternoon when I was walking in, you just feel it with all the people here. You know, we talk to so many different companies on the Q Paul. Every company these days has to be a data company. The most important thing about data is making sure that it's backed up and it's protected, that it's secure, that it can be recovered if anything happens. So we're gonna be having a great conversation next about data resiliency with one of our alumni. >>And that would be Rick Scott, Rick, excuse me, Rick Scott, >>Rick Clark. Rick Clark, say Rick Scott, cloud sales Veritas. Rick, welcome back >>To the program. Thank you. Thank you so much. It's a pleasure being here, you know, thank you so much. You're definitely very excited to myself and 40,000 of my closest cousins and friends all in one place. Yep. Or I could possibly go wrong, right? So >>Yeah, absolutely nothing. So, Rick, so Veritas has made some exciting announcements. Talk to us about some of the new things that you've >>Unveiled. Yeah, we've been, we've been incredibly busy and, you know, the journey that we've been on, one of the big announcement that we made about three or four weeks ago is the introduction, really, of a brand new cloud native data management platform that we call Veritas Alta. And this is a journey that we've been on for the better part of seven years. We actually started it with our, our flex appliances. We continued, that was a containerization of our traditional net backup business in, into a highly secured appliance that was loved by our customers. And we continued that theme and that investment into what we call a scale out and scale up form factor appliance as well, what we called flex scale. And then we continued on that investment theme, basically spending over a billion dollars over that seven year journey in our cloud native. And we call that basically the Veritas altar platform with our cloud native platform. And I think if you really look at what that is, it truly is a data management platform. And I emphasize the term cloud native. And so our traditional technologies around data protection, obviously application resiliency and digital compliance or data compliance and governance. We are the only, the first and only company in the world to provide really a cloud optimized, cloud native platform, really, that addresses that. So it's been fun, it's been a fun journey. >>Talk a little bit about the customer experience. I see over 85% of the Fortune 100 trust Veritas with their data management. That's >>A big number. Yeah. Yeah. It's, it is incredible actually. And it really comes back to the Veritas older platform. We sort of built that with, with four tenants in mind, all driving back to this very similar to AWS's customer obsession. Everything we do each and every day of our waiting moments is a Veritas employee is really surrounds the customer. So it starts with the customer experience on how do they find us to, how do they procure our solutions through things like AWS marketplace and how do they deploy it? And the second thing is around really cost optimization, as we know, you know, to, to say that companies are going through a digital transformation and moving workloads to the cloud. I mean, I've got customers that literally were 20% in cloud a year ago and 80% a year later, we've never seen that kind of velocity. >>And so we've doubled down on this notion of cost optimization. You can only do that with these huge investments that I talked about. And so we're a very profitable company. We've been around, got a great heritage of over 30 years, and we've really taken those investments in r and d to provide that sort of cloud native technology to ultimately make it elastic. And so everything from will spin up and spin down services to optimize the cloud bill for our customers, but we'll also provide the greatest workload support. You know, obviously on-prem workloads are very different from cloud workloads and it's almost like turning the clock back 20 years to see all of those new systems. There's no standard API like s and MP on the network. And so we have to talk to every single PAs service, every single DB PAs, and we capture that information and protect it. So it's really has been a phenomenal journey. It's been great. >>You said this, that that al represents a shift from clouds from flex scale to cloud native. What is the difference there? >>The, the main difference really is we took, you know, obviously our traditional product that you've known for many media years, net backup. It's got, you know, tens of millions of lines of code in that. And we knew if we lifted and shifted it up into the cloud, into an I AEs infrastructure, it's just not, it obviously would perform extremely well, but it wasn't cost optimized for our customer. It was too expensive to to run. And so what we did is we rewrote with microservices and containerization, Kubernetes huge parts of that particular product to really optimize it for the cloud. And not only have we done it for that technology, what we now call alter data protection, but we've done it across our entire port portfolio. That was really the main change that we made as part of this particular transition. And >>What have you done to prepare customers for that shift? Is this gonna be a, a drop in simple upgrade for them? >>Absolutely. Yeah. In fact, one of the things that we introduced is we, we invest still very heavily with regards to our OnPrem solutions. We're certainly not abandoning, we're still innovating. There's a lot of data still OnPrem that needs to move to the cloud. And so we have a unique advantage of all of the different workload supports that we provide OnPrem. We continue that expansion into the cloud. So we, we create it as part of the Veritas AL Vision, a technology, we call it AL view. So it's a single painter glass across both OnPrem and cloud for our customers. And so now they can actually see all of their data protection, all our application availability, single collect, all through that single unified interface, which is really game changing in the industry for us. >>It's game changing for customers too, because customers have what generally six to seven different backup technologies in their environment that they're having to individually manage and provision. So the, the workforce productivity improvements I can imagine are, are huge with Veritas. >>Yeah. You you nailed it, right? You must have seen my script, but Absolutely. I mean, I look at the analogy of, you think about the airlines, what's one of the first things airlines do with efficiency? South Southwest Airlines was the best example, a standardized on the 7 37, right? And so all of their pilots, all of their mechanics, all know how to operate the 7 37. So we are doing the same thing with enterprise data protection. So whether you're OnPrem at the edge or in the cloud or even multi-cloud, we can provide that single painter glass. We've done it for our customers for 30 plus years. We'll continue to do it for another 30 something years. And so it's really the first time with Veritas altar that, that we're, we're coming out with something that we've invested for so long and put, put such a huge investment on that can create those changes and that compelling solution for our customers. So as you can see, we're pretty pumped and excited about it. >>Yes, I can >>Use the term data management to describe Alta, and I want to ask about that term because I hear it a lot these days. Data management used to be database, now data management is being applied to all kinds of different functions across the spectrum. How do you define data management in Veritas >>Perspective? Yeah, there's a, we, we see it as really three main pillars across the environment. So one is protection, and we'll talk a little bit about this notion of ransomware is probably the number one use case. So the ability to take the most complex and the biggest, most vast applications. SAP is an example with hundreds of different moving parts to it and being able to protect that. The second is application resiliency. If, if you look at the cloud, there's this notion of, of responsibility, shared responsibility in the cloud. You've heard it, right? Yep. Every single one of the cloud service providers, certainly AWS has up on their website, this is what we protect, here's the demarcation line, the line in the sand, and you, the customer are responsible for that other level. And so we've had a technology, you previously knew it as InfoScale, we now call it alter application resiliency. >>And it can provide availability zone to availability zone, real time replication, high availability of your mission critical applications, right? So not only do we do the traditional backups, but we can also provide application resiliency for mission critical. And then the third thing really from a data management standpoint is all around governance and compliance. You know, ac a lot of our customers need to keep data for five, 10 years or forever. They're audited. There's regulations and different geographies around the world. And, and those regulations require them to be able to really take control of their cloud, take control of their data. And so we have a whole portfolio of solutions under that data compliance, data government. So back to your, your question Paul, it's really the integration and the intersection of those three main pillars. We're not a one trick pony. We've been at this for a long time, and they're not just new products that we invented a couple of months ago and brought to market. They're tried and tested with eight 80,000 customers and the most complex early solutions on the planet that we've been supporting. >>I gotta ask you, you know, we talked about those three pillars and you talked about the shared responsibility model. And think of that where you mentioned aws, Salesforce, Microsoft 365, Google workspace, whatnot. Are you finding that most customers aren't aware of that and haven't been protecting those workloads and then come to you and saying, Hey guys, guess what, this is what this is what they're responsible for. The data is >>You Yeah, I, it's, it's our probably biggest challenge is, is one of awareness, you know, with the cloud, I mean, how many times have you spoken to someone? You just put it in the cloud. Your applications, like the cloud providers like aws, they'll protect everything. Nothing will ever go down. And it's kind like if you, unless your house was ever broken into, you're probably not gonna install that burglar alarm or that fire alarm, right? Hopefully that won't be an event that you guys have to suffer through. So yeah, it's definitely, it wasn't till the last year or so the cloud service providers really published jointly as to where is their responsibility, right? So a great example is an attack vector for a lot of corporations is their SAS applications. So, you know, whether it it's your traditional SA applications that is available that's available on the web to their customers as a sas. >>And so it's certainly available to the bad actors. They're gonna, where there's, there's gonna be a point they're gonna try to get in. And so no matter what your resiliency plan is, at the end of the day, you really need to protect it. And protection isn't just, for example, with M 365 having a snapshot or a recycle bin, that's just not good enough. And so we actually have some pretty compelling technology, what we call ALTA SAS protection, which covers the, pretty much the, the gamut of the major SAS technologies to protect those and make it available for our customers. So yeah, certainly it's a big part of it is awareness. Yeah. >>Well, I understand that the shared responsibility model, I, I realize there's a lot of confusion about that still, but in the SaaS world that's somewhat different. The responsibility of the SaaS provider for protecting data is somewhat different. How, how should, what should customers know about that? >>I think, you know, the, the related to that, if, if you look at OnPrem, you know, approximately 35 to 40% of OnPrem enterprise data is protected. It's kind of in a long traditional problem. Everyone's aware of it. You know, I remember going to a presentation from IBM 20 something years ago, and someone held their push hand up in the room about the dis drives and says, you need to back it up. And the IBM sales guy said, no, IBM dis drives never crash. Right? And so fast forward to here we are today, things have changed. So we're going through almost a similar sort of changes and culture in the cloud. 8% of the data in the cloud is protected today, 8%. That's incredible. Meaning >>That there is independent backup devoted >>To that data in some cases, not at all. And something many cases, the customer just assumes that it's in the cloud, therefore it's always available. I never have to worry about protecting it, right? And so that's a big problem that we're obviously trying to, trying to solve. And we do that all under the umbrella of ransomware. That's a huge theme, huge investment that, that Veritas does with regards to providing that resiliency for our >>Customers. Ransomware is scary. It is becoming so prolific. The bad actors have access to technologies. Obviously companies are fighting them, but now ransomware has evolved into, no longer are we gonna get hit, it's when, yeah, it's how often it's what's the damage going to be. So the ability to help customers recover from ransomware, that resiliency is table stakes for businesses in any industry these days. Does that, that one of the primary pain points that your customers are coming to you with? >>It's the number one pain point. Yeah, it's, it's incredible. I mean, there's not a single briefing that our teams are doing customer meetings where that term ransomware doesn't come up as, as their number one use case. Just to give you something, a couple of statistics. There's a ransomware attack attack that happens 11 times a second right around the globe. And this isn't just, you know, minor stuff, right? I've got friends that are, you know, executives of large company that have been hit that have that some, you know, multimillion dollar ransom attack. So our, our play on this is, when you think about it, is data protection is the last line of defense. Yes. And so if they break through, it's not a case, Lisa, as you mentioned, if it's a case of when Yeah. And so it's gonna happen. So one of the most important things is knowing how do you know you have a gold copy, a clean copy, and you can recover at speed in some cases. >>We're talking about tens of thousands of systems to do that at speed. That's in our dna. We've been doing it for many, many years. And we spoke through a lot of the cyber insurance companies on this particular topic as well. And what really came back from that is that they're actually now demanding things like immutable storage, malware detection, air gaping, right? Anomaly detection is sort of core technologies tick the box that they literally won't ensure you unless you have those core components. And so what we've done is we've doubled down on that investment. We use AI in ML technologies, particularly around the anomaly detection. One of the, the, the unique and ne differentiators that Verto provides is a ransomware resiliency scorecard. Imagine the ability to save uran a corporation. We can come in and run our analytics on your environment and kind of give you a grade, right? Wouldn't you prefer that than waiting for the event to take place to see where your vulnerability really is? And so these are some of the advantages that we can actually provide for our customers, really, really >>To help. Just a final quick question. There is a, a common perception, I believe that ransomware is an on premise problem. In fact, it is also a cloud problem. Is that not right? >>Oh, absolutely. I I think that probably the biggest attack vector is in the cloud. If it's, if it's OnPrem, you've certainly got a certain line of defense that's trying to break through. But, you know, you're in the open world there. Obviously with SAS applications in the cloud, it's not a case of if, but when, and it's, and it's gonna continue to get, you know, more and more prevalent within corporations. There's always gonna be those attack factors that they find the, the flash wounds that they can attack to break through. What we are concentrating on is that resiliency, that ability for customers to recover at speed. We've done that with our traditional appliances from our heritage OnPrem. We continue to do that with regard to resiliency at speed with our customers in the cloud, with partners like aws >>For sure. Almost done. Give me your 30 seconds on AWS and Veritas. >>We've had a partnership for the better part of 10 years. It's incredible when you think about aws, where they released the elastic compute back in 2006, right? We've been delivering data protection, a data management solutions for, for the better part of 30 years, right? So, so we're, we're Junos in our space. We're the leader in, in data protection and enterprise data protection. We were on-prem. We, we continue to be in the cloud as AWS was with the cloud service provided. So the synergies are incredible. About 80 to 85% of our, our joint customers are the same. We take core unique superpowers of aws, like AWS outposts and AWS Glacier Instant retrieval, for example, those core technologies and incorporate them into our products as we go to Mark. And so we released a core technology a few months ago, we call it ultra recovery vault. And it's an air gap, a mutable storage, worm storage, right Once, right? You can't change it even when the bad actors try to get in. They're independent from the customer's tenant and aws. So we manage it as a managed backup service for our customers. Got it. And so our customers are using that to really help them with their ransomware. So it's been a tremendous partnership with AWS >>Standing 10 years of accounting. Last question for you, Rick. You got a billboard on the 1 0 1 in Santa Clara, right? By the fancy Verto >>1 0 1? >>Yeah. Right. Well, there's no traffic. What does that billboard say? What's that bumper sticker about? Vertus, >>I think, I think the billboard would say, welcome to the new Veritas. This is not your grandfather's old mobile. We've done a phenomenal job in, in the last, particularly the last three or four years, to really reinvent ourselves in the cloud and the investments that we made are really paying off for our customers today. So I'm excited to be part of this journey and excited to talk to you guys today. >>Love it. Not your grandfather's Veritas. Rick, thank you so much for joining Paula, me on the forgot talking about what you guys are doing, how you're helping customers, really established that cyber of resiliency, which is absolutely critical these days. We appreciate your >>Time. My pleasure. Thank you so much. >>All right, for our guest and Paul Gilland, I'm Lisa Martin, you're watching the Queue, which as you know is the leader in live enterprise and emerging check coverage.

>>Hey everyone, and welcome back to Las Vegas. Viva Las Vegas, baby. This is the Cube live at AWS Reinvent 2022 with tens of thousands of people. Lisa Martin here with Dave Valante. Dave, we've had some great conversations. This is day one of four days of wall to wall coverage on the cube. We've been talking data. Every company is a data company. Data protection, data resiliency, absolutely table stakes for organizations to, >>And I think ecosystem is the other big theme. And that really came to life last year. You know, we came out of the pandemic and it was like, wow, we are entering a new era. People no longer was the ecosystem worried about it, AWS competing with them. They were more worried about innovating and building on top of AWS and building their own value. And that's really, I think, the theme of the 2020s within the ecosystem. >>And we're gonna be talking about building on top of aws. Two guests join us, two alumni join us. Stephen Manley is here, the CTO of Druva. Welcome back. Jason crat as well is here. CIO and CTO of Summit Carbon Solutions. Guys, great to have you back on the program. >>Thank you. >>Let's start with you giving the audience an understanding of the company. What do you guys do? What do you deliver value for customers? All that good >>Stuff. Yeah, no, for sure. So Summit Carbon is the world's largest carbon capture and sequestration company capturing close to 15 million tons of carbon every year. So it doesn't go into the atmosphere. >>Wow, fantastic. Steven, the, the risk landscape today is crazy, right? There's, there's been massive changes. We've talked about this many times. What are some of the things, you know, ransomware is a, is, I know as you say, this is a, it's not a, if it's gonna happen, it's when it's how frequent, it's what's gonna be the damage. What are some of the challenges and concerns that you're hearing from customers out there today? >>Yeah, you know, it really comes down to three things. And, and everybody is, is terrified of ransomware and justifiably so. So, so the first thing that comes up is, how do I keep up? Because I have so much data in so many places, and the threats are evolving so quickly. I don't have enough money, I don't have enough people, I don't have enough skilled resources to be able to keep up. The second thing, and this ties in with what Dave said, is, is ecosystem. You know, it used to be that your, your backup was siloed, right? They'd sit in the basement and, and you wouldn't see, see them. But now they're saying, I've gotta work with my security team. So rather than hoping the security team stays away from me, how do I integrate with them? How do I tie together? And then the third one, which is on everybody's mind, is when that attack happens, and like you said, it's win and, and the bell rings and they come to me and they say, all right, it's time for you to recover. It's time for, for all this investment we've put in. Am I gonna be ready? Am I going to be able to execute? Because a ransom or recovery is so different than any other recovery they've ever done. So it's those three things that really are top of mind for >>How, so what is the, what are the key differences, if you could summarize? I mean, I >>Know it's so, so the first one is you can't trust the environment you're restoring into. Even with a disaster, it would finish and you'd say, okay, I'm gonna get my data center set up again and I'm gonna get things working. You know, when I try to recover, I don't know if everything's clean yet. I'm trying to recover while I'm still going through incident response. So that's one big difference. A second big difference is I'm not sure if the thing I'm recovering is good, I've gotta scan it. I've gotta make sure what's inside it is, is, is alright. And then the third thing is what we're seeing is the targets are usually not necessarily the crown jewels because those tend to be more protected. And so they're running into this, I need to recover a massive amount of what we might call tier two, tier three apps that I wasn't ready for because I've always been prepared for that tier one disaster. And so, so those three things they go, it's stuff I'm not prepared or covering. It's a flow. I'm not used to having to check things and I'm not sure where I'm gonna recover too when the, when the time comes. >>Yeah, just go ahead. Yeah, that's right. I mean, I think for me, the biggest concern is the blind spots of where did I actually back it up or not. You know, what did I get it? Cuz you, we always protect our e r p, we always protect these sort of classes of tiers of systems, but then it's like, oh, that user's email box didn't get it. Oh, that, you know, that one drive didn't get it. You know, or, or, or whatever it is. You know, the infrastructure behind it all. I forgot to back that up. That to me the blind spots are the scariest part of a ransomware attack. >>And, and if you think about it, some of the most high profile attacks, you know, on the, on the colonial pipeline, they didn't go after the core assets. They went after billing. That's right. But billing brought everything down so they're smart enough to say, right, I'm not gonna take the, the castle head on. Is there is they're that. Exactly. >>And so how do you, I get, I mean you can air gap and do things like that in terms of protecting the, the, the data, the corrupt data. How do you protect the corrupt environment? Like that's, that's a really challenging issue. Is >>It? I don't know. I mean, I'll, I'll you can go second here. I think that what's interesting to me about is that's what cloud's for. You can build as many environments as you want. You only pay for what you use, right? And so you have an opportunity to just reconstruct it. That's why things, everything is code matters. That's why having a cloud partner like Druva matters. So you can just go restore wherever you need to in a totally clean environment. >>So the answer is you gotta do it in the cloud. Yeah. What if it's on prem? >>So if it's on prem, what we see people do is, and, and, and this is where testing and, and where cloud can still be an asset, is you can look and say a lot of those assets I'm running in the data center, I could still recover in the cloud. And so you can go through DR testing and you can start to define what's in your on-prem so that you could make it, you know, so you can make it cloud recoverable. Now, a lot of the people that do that then say, well actually why am I even running this on prem anymore in the first place? I should just move this to the cloud now. But, but, but there are people in that interim step. But, but, but it's really important because you, you're gonna need a clean environment to play in. And it's so hard to have a clean environment set up in a data center cuz it basically means I'm not touching this, I'm just paying for something to sit idle. Whereas cloud, I can spin that up, right? Get a, a cloud foundation suite and, and just again, infrastructures code, spin things up, test it, spin it down. It doesn't cost me money on a daily basis. >>Jason, talk a little bit about how you are using Druva. Why Druva and give us a kind of a landscape of your IT environment with Druva. >>Yeah. You know, so when we first started, you know, we did have a competitor solution and, and, and it was only backing up, you know, we were a startup. It was only backing up our email. And so as you pointed out, the ecosystem really matters because we grew out of email pretty quick as a startup. And we had to have real use cases to protect and the legacy product just wouldn't support us. And so our whole direction, or my direction to my team is back it up wherever it is, you know, go get it. And so we needed somebody in the field, literally in the middle of Nebraska or Iowa to have their laptop backed up. We needed our infrastructure, our data center backed up and we needed our, our SaaS solutions backed up. We needed it all. And so we needed a partner like Druva to help us go get it wherever it's at. >>Talk about the value in, with Druva being cloud native. >>Yeah. To us it's a big deal, right? There's all sorts of products you could go by to go just do endpoint laptop protection or just do SAS backups. For us, the value is in learning one tool and mastering it and then taking it to wherever the data is. To me, we see a lot of value for that because we can have one team focus on one product, get good at it, and drive the value. >>That consolidation theme is big right now, you know, the economic headwinds and so forth. What was the catalyst for you? Was it, is that something you started, you know, years ago? Just it's good practice to do that? What's, >>Well, no, I mean luckily I'm in a very good position as a startup to do define it, you know, but I've been in those legacy organizations where we've got a lot of tech debt and then how do you consolidate your portfolio so that you can gain more value, right? Cause you only get one budget a year, right? And so I'm lucky in, in the learnings I've had in other enterprises to deal with this head on right now as we grow, don't add tech debt, put it in right. Today. >>Talk to us a little bit about the SaaS applications that you're backing up. You know, we, we talk a lot with customers, the shared, the shared responsibility model that a lot of customers aren't aware of. Where are you using that competing solution to protect SaaS applications before driven and talk about Yeah. The, the value in that going, the data protection is our responsibility and not the SA vendor. >>No, absolutely. I mean, and it is funny to go to, you know, it's like Office 365 applications and go to our, our CFO and a leadership and be like, no, we really gotta back it up to a third party. And they're like, but why? >>It's >>In the cloud, right? And so there's a lot of instruction I have to provide to my peers and, and, and my users to help them understand why these things matter. And, and, and it works out really well because we can show value really quick when anything happens. And now we get, I mean, even in SharePoint, people will come to us to restore things when they're fully empowered to do it. But my team's faster. And so we can just get it done for them. And so it's an extra from me, it's an extra SLA or never service level I can provide to my internal customers that, that gives them more faith and trust in my organization. >>How, how are the SEC op teams and the data protection teams, the backup teams, how are they coming together? Is is, is data protection backup just morphing into security? Is it more of an adjacency? What's that dynamic like? >>So I'd say right now, and, and I'll be curious to hear Jason's organization, but certainly what we see broadly is, you know, the, the teams are starting to work together, but I wouldn't say they're merging, right? Because, you know, you think of it in a couple of ways. The first is you've got a production environment and that needs to be secured. And then you've got a protection environment. And that protection environment also has to be secured. So the first conversation for a lot of backup teams is, alright, I need to actually work with the security team to make sure that, that my, my my backup environment, it's air gapped, it's encrypted, it's secured. Then I think the, the then I think you start to see people come together, especially as they go through, say, tabletop exercises for ransomware recovery, where it's, alright, where, where can the backup team add value here? >>Because certainly recovery, that's the basics. But as there log information you can provide, are there detection pieces that you can offer? So, so I think, you know, you start to see a partnership, but, but the reality is, you know, the, the two are still separate, right? Because, you know, my job as a a protection resiliency company is I wanna make sure that when you need your data, it's gonna be there for you. And I certainly want to, to to follow best secure practices and I wanna offer value to the security team, but there's a whole lot of the security ecosystem that I want to plug into. I'm not trying to replace them again. I want to be part of that broader ecosystem. >>So how, how do you guys approach it? Yeah, >>That's interesting. Yeah. So in my organization, we, we are one team and, and not to be too cheesy or you know, whatever, but as Amazon would say, security is job one. And so we treat it as if this is it. And so we never push something into production until we are ready. And ready to us means it's got a security package on it, it's backed up, the users have tested it, we are ready to go. It's not that we're ready just be to provide the service or the thing. It's that we are actually ready to productionize this. And so it's ready for production data and that slows us down in some cases. But that's where DevOps and this idea of just merging everything together into a central, how do we get this done together, has worked out really well for us. So, >>So it's really the DevOps team's responsibility. It's not a separate data protection function. >>Nope. Nope. We have specialists of course, right? Yeah, yeah. Because you need the extra level, the CISSPs and those people Yeah, yeah. To really know what they're doing, but they're just part of the team. Yeah. >>Talk about some of the business outcomes that you're achieving with Druva so far. >>Yeah. The business outcomes for me are, you know, I meet my SLAs that's promising. I can communicate that I feel more secure in the cloud and, and all of my workloads because I can restore it. And, and that to me helps everybody in my organization sleep well, sleep better. We are, we transport a lot of the carbon in a pipeline like Colonial. And so to us, we are, we are potential victims of, of a pipe, a non pipeline group, right? Attacking us, but it's carbon, you know, we're trying to get it outta atmosphere. And so by protecting it, no matter where it is, as long as we've got internet access, we can back it up. That provides tons of value to my team because we have hundreds of people in the field working for us every day who collect data and generate it. >>What would you say to a customer who's maybe on the fence looking at different technologies, why dva? >>You know, I think, you know, do the research in my mind, it'll win if you just do the research, right? I mean, there might be vendors that'll buy you nice dinners or whatever, and those are, those are nice things, but the, the reality is you have to protect your data no matter where it is. If it's in a SaaS application, if it's in a cloud provider, if it's infrastructure, wherever it is, you need it. And if you just go look at the facts, there it is, right? And so I, I'd say be objective. Look at the facts, it'll prove itself. >>Look at the data. There you go. Steven Druva recently announced a data resiliency guarantee with a big whopping financial sum. Talk to us a little bit about that, the value in it for your customers and for prospects, >>Right? So, so basically there's, there's really two parts to this guarantee. The first is, you know, across five different SLAs, and I'll talk about those, you know, if we violate those, the customers can get a payout of up to 10 million, right? So again, putting, putting our money where our mouth is in a pretty large amount. But, but for me, the exciting part, and this is, this is where Jason went, is it's about the SLAs, right? You know, one of Drew's goals is to say, look, we do the job for you, we do the service for you so you can offer that service to your company. And so the SLAs aren't just about ransomware, some of them certainly are, you know, that, that you're going to be able to recover your data in the event of a ransomware attack, that your data won't get exfiltrated as part of a ransomware attack. >>But also things like backup success rates, because as much as recovery matters a lot more than backup, you do need a backup if you're gonna be able to get that recovery done. There's also an SLA to say that, you know, if 10 years down the road you need to recover your data, it's still recoverable, right? So, so that kind of durability piece. And then of course the availability of the service because what's the point of a service if it's not there for you when you need it? And so, so having that breadth of coverage, I think really reflects who Druva is, which is we're doing this job for you, right? We want to make this this service available so you can focus on offering other value inside your business. And >>The insurance underwriters, if they threw holy water on >>That, they, they, they were okay with it. The legal people blessed it, you know, it, you know, the CEO signed off on it, the board of directors. So, you know, it, and it, it's all there in print, it's all there on the web. If you wanna look, you know, make sure, one of the things we wanted to be very clear on is that this isn't just a marketing gimmick that we're, we're putting, that we're putting substance behind it because a lot of these were already in our contracts anyway, because as a SAS vendor, you're signing up for service level agreements anyway. >>Yeah. But most of the service level agreements and SaaS vendors are crap. They're like, you know, hey, you know, if something bad happens, you know, we'll, we'll give you a credit, >>Right? >>For, you know, for when you were down. I mean, it's not, you never get into business impact. I mean, even aws, sorry, I mean, it's true. We're a customer. I read define print, I know what I'm signing up for. But, so that's, >>We read it a lot and we will not, we don't really care about the credits at all. We care about is it their force? Is it a partner? We trust, we fight that every day in our SLAs with our vendors >>In the end, right? I mean this, we are the last line of defense. We are the thing that keeps the business up and running. So if your business, you know, can't get to his data and can't operate, me coming to you and saying, Dave, I've got some credits for you after you, you know, after you declare bankruptcy, it'll be great. Yeah, that's not a win. >>It's no value, >>Not helpful. The goal's gotta be, your business is up and running cuz that's when we're both successful. So, so, so, you know, we view this as we're in it together, right? We wanna make sure your business succeeds. Again, it's not about slight of hand, it's not about, you know, just, just putting fine print in the contract. It's about standing up and delivering. Because if you can't do that, why are we here? Right? The number one thing we hear from our customers is Dr. Just works. And that's the thing I think I'm most proud of is Druva just works. >>So, speaking of Juva, just working, if there's a billboard in Santa Clara near the new offices about Druva, what's, what's the bumper sticker? What's the tagline? >>I, I, I think, I think that's it. I think Druva just works. Keeps your data safe. Simple as that. Safe and secure. Druva works to keep your data safe and secure. >>Saved me. >>Yeah. >>Truva just works. Guys, thanks so much for joining. David, me on the program. Great to have you back on the cube. Thank you. Talking about how you're working together, what Druva is doing to really putting, its its best foot forward. We appreciate your insights and your time. Thank >>You. Thanks guys. It's great to see you guys. Likewise >>The show for our guests and Dave Ante. I'm Lisa Martin, you're watching the Cube, the leader in enterprise and emerging tech coverage.

(upbeat music) >> Welcome back. We're here at Supercomputing 22 in Dallas. My name's Paul Gill, I'm your host. With me, Dave Nicholson, my co-host. And one thing that struck me about this conference arriving here, was the number of universities that are exhibiting here. I mean, big, big exhibits from universities. Never seen that at a conference before. And one of those universities is Indiana University. Our two guests, Dave Jent, who's the AVP of Networks at Indiana University, Aaron Neal, Deputy CIO at Indiana University. Welcome, thanks for joining us. >> Thank you for having us. >> Thank you. >> I've always thought that the CIO job at a university has got to be the toughest CIO job there is, because you're managing this sprawling network, people are doing all kinds of different things on it. You've got to secure it. You've got to make it performant. And it just seems to be a big challenge. Talk about the network at Indiana University and what you have done particularly since the pandemic, how that has affected the architecture of your network. And what you do to maintain the levels of performance and security that you need. >> On the network side one of the things we've done is, kept in close contact with what the incoming students are looking for. It's a different environment than it was then 10 years ago when a student would come, maybe they had a phone, maybe they had one laptop. Today they're coming with multiple phones, multiple laptops, gaming devices. And the expectation that they have to come on a campus and plug all that stuff in causes lots of problems for us, in managing just the security aspect of it, the capacity, the IP space required to manage six, seven devices per student when you have 35,000 students on campus, has always been a challenge. And keeping ahead of that knowing what students are going to come in with, has been interesting. During the pandemic the campus was closed for a bit of time. What we found was our biggest challenge was keeping up with the number of people who wanted to VPN to campus. We had to buy additional VPN licenses so they could do their work, authenticate to the network. We doubled, maybe even tripled our our VPN license count. And that has settled down now that we're back on campus. But again, they came back with a vengeance. More gaming devices, more things to be connected, and into an environment that was a couple years old, that we hadn't done much with. We had gone through a pretty good size network deployment of new hardware to try to get ready for them. And it's worked well, but it's always challenging to keep up with students. >> Aaron, I want to ask you about security because that really is one of your key areas of focus. And you're collaborating with counties, local municipalities, as well as other educational institutions. How's your security strategy evolving in light of some of the vulnerabilities of VPNs that became obvious during the pandemic, and this kind of perfusion of new devices that that Dave was talking about? >> Yeah, so one of the things that we we did several years ago was establish what we call OmniSOC, which is a shared security operations center in collaboration with other institutions as well as research centers across the United States and in Indiana. And really what that is, is we took the lessons that we've learned and the capabilities that we've had within the institution and looked to partner with those key institutions to bring that data in-house, utilize our staff such that we can look for security threats and share that information across the the other institutions so that we can give each of those areas a heads up and work with those institutions to address any kind of vulnerabilities that might be out there. One of the other things that you mentioned is, we're partnering with Purdue in the Indiana Office of Technology on a grant to actually work with municipalities, county governments, to really assess their posture as it relates to security in those areas. It's a great opportunity for us to work together as institutions as well as work with the state in general to increase our posture as it relates to security. >> Dave, what brings IU to Supercomputing 2022? >> We've been here for a long time. And I think one of the things that we're always interested in is, what's next? What's new? There's so many, there's network vendors, software vendors, hardware vendors, high performance computing suppliers. What is out there that we're interested in? IU runs a large Cray system in Indiana called Big Red 200. And with any system you procure it, you get it running, you operate it, and your next goal is to upgrade it. And what's out there that we might be interested? That I think why we come to IU. We also like to showcase what we do at IU. If you come by the booth you'll see the OmniSOC, there's some video on that. The GlobalNOC, which I manage, which supports a lot of the RNE institutions in the country. We talk about that. Being able to have a place for people to come and see us. If you stand by the booth long enough people come and find you, and want to talk about a project they have, or a collaboration they'd like to partner with. We had a guy come by a while ago wanting a job. Those are all good things having a big booth can do for you. >> Well, so on that subject, in each of your areas of expertise and your purview are you kind of interleaved with the academic side of things on campus? Do you include students? I mean, I would think it would be a great source of cheap labor for you at least. Or is there kind of a wall between what you guys are responsible for and what students? >> Absolutely we try to support faculty and students as much as we can. And just to go back a little bit on the OmniSOC discussion. One of the things that we provide is internships for each of the universities that we work with. They have to sponsor at least three students every year and make that financial commitment. We bring them on site for three weeks. They learn us alongside the other analysts, information security analysts and work in a real world environment and gain those skills to be able to go back to their institutions and do an additional work there. So it's a great program for us to work with students. I think the other thing that we do is we provide obviously the infrastructure that enable our faculty members to do the research that they need to do. Whether that's through Big Red 200, our Supercomputer or just kind of the everyday infrastructure that allows them to do what they need to do. We have an environment on premise called our Intelligent Infrastructure, that we provide managed access to hardware and storage resources in a way that we know it's secure and they can utilize that environment to do virtually anything that they need in a server environment. >> Dave, I want to get back to the GigaPOP, which you mentioned earlier you're the managing director of the Indiana GigaPOP. What exactly is it? >> Well, the GigaPOP and there are a number of GigaPOP around the country. It was really the aggregation facility for Indiana and all of the universities in Indiana to connect to outside resources. GigaPOP has connections to internet too, the commodity internet, Esnet, the Big Ten or the BTAA a network in Chicago. It's a way for all universities in Indiana to connect to a single source to allow them to connect nationally to research organizations. >> And what are the benefits of having this collaboration of university. >> If you could think of a researcher at Indiana wants to do something with a researcher in Wisconsin, they both connect to their research networks in Wisconsin and Indiana, and they have essentially direct connection. There's no commodity internet, there's no throttling of of capacity. Both networks and the interconnects because we use internet too, are essentially UNT throttled access for the researchers to do anything they need to do. It's secure, it's fast, easy to use, in fact, so easy they don't even know that they're using it. It just we manage the networks and organize the networks in a way configure them that's the path of least resistance and that's the path traffic will take. And that's nationally. There are lots of these that are interconnected in various ways. I do want to get back to the labor point, just for a moment. (laughs) Because... >> You're here to claim you're not violating any labor laws. Is that what you're going to be? >> I'm here to hopefully hire, get more people to be interested to coming to IU. >> Stop by the booth. >> It's a great place to work. >> Exactly. >> We hire lots of interns and in the network space hiring really experienced network engineers, really hard to do, hard to attract people. And these days when you can work from anywhere, you don't have to be any place to work for anybody. We try to attract as many students as we can. And really we're exposing 'em to an environment that exists in very few places. Tens of thousands of wireless access points, big fast networks, interconnections and national international networks. We support the Noah network which supports satellite systems and secure traffic. It really is a very unique experience and you can come to IU, spend lots of years there and never see the same thing twice. We think we have an environment that's really a good way for people to come out of college, graduate school, work for some number of years and hopefully stay at IU, but if not, leave and get a good job and talk well about IU. In fact, the wireless network today here at SC was installed and is managed by a person who manages our campus network wireless, James Dickerson. That's the kind of opportunity we can provide people at IU. >> Aaron, I'd like to ask, you hear a lot about everything moving to the cloud these days, but in the HPC world I don't think that move is happening as quickly as it is in some areas. In fact, there's a good argument some workloads should never move to the cloud. You're having to balance these decisions. Where are you on the thinking of what belongs in the data center and what belongs in the cloud? >> I think our approach has really been specific to what the needs are. As an institution, we've not pushed all our chips in on the cloud, whether it be for high performance computing or otherwise. It's really looking at what the specific need is and addressing it with the proper solution. We made an investment several years ago in a data center internally, and we're leveraging that through the intelligent infrastructure that I spoke about. But really it's addressing what the specific need is and finding the specific solution, rather than going all in in one direction or another. I dunno if Jet Stream is something that you would like to bring up as well. >> By having our own data center and having our own facilities we're able to compete for NSF grants and work on projects that provide shared resources for the research community. Just dream is a project that does that. Without a data center and without the ability to work on large projects, we don't have any of that. If you don't have that then you're dependent on someone else. We like to say that, what we are proud of is the people come to IU and ask us if they can partner on our projects. Without a data center and those resources we are the ones who have to go out and say can we partner on your project? We'd like to be the leaders of that in that space. >> I wanted to kind of double click on something you mentioned. Couple of things. Historically IU has been I'm sure closely associated with Chicago. You think of what are students thinking of doing when they graduate? Maybe they're going to go home, but the sort of center of gravity it's like Chicago. You mentioned talking about, especially post pandemic, the idea that you can live anywhere. Not everybody wants to live in Manhattan or Santa Clara. And of course, technology over decades has given us the ability to do things remotely and IU is plugged into the globe, doesn't matter where you are. But have you seen either during or post pandemic 'cause we're really in the early stages of this. Are you seeing that? Are you seeing people say, Hey, thinking about their family, where do I want to live? Where do I want to raise my family? I'm in academia and no, I don't want to live in Manhattan. Hey, we can go to IU and we're plugged into the globe. And then students in California we see this, there's some schools on the central coast where people loved living there when they were in college but there was no economic opportunity there. Are you seeing a shift, are basically houses in Bloomington becoming unaffordable because people are saying, you know what, I'm going to stay here. What does that look like? >> I mean, for our group there are a lot of people who do work from home, have chosen to stay in Bloomington. We have had some people who for various reasons want to leave. We want to retain them, so we allow them to work remotely. And that has turned into a tool for recruiting. The kid that graduates from Caltech. Doesn't want to stay in Caltech in California, we have an opportunity now he can move to wherever between here and there and we can hire him do work. We love to have people come to Indiana. We think it is a unique experience, Bloomington, Indianapolis are great places. But I think the reality is, we're not going to get everybody to come live, be a Hoosier, how do we get them to come and work at IU? In some ways disappointing when we don't have buildings full of people, but 40 paying Zoom or teams window, not kind the same thing. But I think this is what we're going to have to figure out, how do we make this kind of environment work. >> Last question here, give you a chance to put in a plug for Indiana University. For those those data scientists those researchers who may be open to working somewhere else, why would they come to Indiana University? What's different about what you do from what every other academic institution does, Aaron? >> Yeah, I think a lot of what we just talked about today in terms of from a network's perspective, that were plugged in globally. I think if you look beyond the networks I think there are tremendous opportunities for folks to come to Bloomington and experience some bleeding edge technology and to work with some very talented people. I've been amazed, I've been at IU for 20 years and as I look at our peers across higher ed, well, I don't want to say they're not doing as well I do want brag at how well we're doing in terms of organizationally addressing things like security in a centralized way that really puts us in a better position. We're just doing a lot of things that I think some of our peers are catching up to and have been catching up to over the last 10, 12 years. >> And I think to sure scale of IU goes unnoticed at times. IU has the largest medical school in the country. One of the largest nursing schools in the country. And people just kind of overlook some of that. Maybe we need to do a better job of talking about it. But for those who are aware there are a lot of opportunities in life sciences, healthcare, the social sciences. IU has the largest logistics program in the world. We teach more languages than anybody else in the world. The varying kinds of things you can get involved with at IU including networks, I think pretty unparalleled. >> Well, making the case for high performance computing in the Hoosier State. Aaron, Dave, thanks very much for joining you making a great case. >> Thank you. >> Thank you. >> We'll be back right after this short message. This is theCUBE. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Virtually all tech companies have expressed caution in their respective earnings calls, and why not? I know you're sick in talking about the macroeconomic environment, but it's full of uncertainties and there's no upside to providing aggressive guidance when sellers are in control. They punish even the slightest miss. Moreover, the spending data confirms the softening market across the board, so it's becoming expected that CFOs will guide cautiously. But companies facing execution challenges, they can't hide behind the macro, which is why it's important to understand which firms are best positioned to maintain momentum through the headwinds and come out the other side stronger. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this "Breaking Analysis," we'll do three things. First, we're going to share a high-level view of the spending pinch that almost all sectors are experiencing. Second, we're going to highlight some of those companies that continue to show notably strong momentum and relatively high spending velocity on their platforms, albeit less robust than last year. And third, we're going to give you a peak at how one senior technology leader in the financial sector sees the competitive dynamic between AWS, Snowflake, and Databricks. So I landed on the red eye this morning and opened my eyes, and then opened my email to see this. My Barron's Daily had a headline telling me how bad things are and why they could get worse. The S&P Thursday hit a new closing low for the year. The safe haven of bonds are sucking wind. The market hasn't seemed to find a floor. Central banks are raising rates. Inflation is still high, but the job market remains strong. Oh, not to mention that the US debt service is headed toward a trillion dollars per year, and the geopolitical situation is pretty tense, and Europe seems to be really struggling. Yeah, so the Santa Claus rally is really looking pretty precarious, especially if there's a liquidity crunch coming, like guess why they call Barron's Barron's. Last week, we showed you this graphic ahead of the UiPath event. For months, the big four sectors, cloud, containers, AI, and RPA, have shown spending momentum above the rest. Now, this chart shows net score or spending velocity on specific sectors, and these four have consistently trended above the 40% red line for two years now, until this past ETR survey. ML/AI and RPA have decelerated as shown by the squiggly lines, and our premise was that they are more discretionary than the other sectors. The big four is now the big two: cloud and containers. But the reality is almost every sector in the ETR taxonomy is down as shown here. This chart shows the sectors that have decreased in a meaningful way. Almost all sectors are now below the trend line and only cloud and containers, as we showed earlier, are above the magic 40% mark. Container platforms and container orchestration are those gray dots. And no sector has shown a significant increase in spending velocity relative to October 2021 survey. In addition to ML/AI and RPA, information security, yes, security, virtualizations, video conferencing, outsourced IT, syndicated research. Syndicated research, yeah, those Gartner, IDC, Forrester, they stand out as seemingly the most discretionary, although we would argue that security is less discretionary. But what you're seeing is a share shift as we've previously reported toward modern platforms and away from point tools. But the point is there is no sector that is immune from the macroeconomic environment. Although remember, as we reported last week, we're still expecting five to 6% IT spending growth this year relative to 2021, but it's a dynamic environment. So let's now take a look at some of the key players and see how they're performing on a relative basis. This chart shows the net score or spending momentum on the y-axis and the pervasiveness of the vendor within the ETR survey measured as the percentage of respondents citing the vendor in use. As usual, Microsoft and AWS stand out because they are both pervasive on the x-axis and they're highly elevated on the vertical axis. For two companies of this size that demonstrate and maintain net scores above the 40% mark is extremely impressive. Although AWS is now showing much higher on the vertical scale relative to Microsoft, which is a new trend. Normally, we see Microsoft dominating on both dimensions. Salesforce is impressive as well because it's so large, but it's below those two on the vertical axis. Now, Google is meaningfully large, but relative to the other big public clouds, AWS and Azure, we see this as disappointing. John Blackledge of Cowen went on CNBC this past week and said that GCP, by his estimates, are 75% of Google Cloud's reported revenue and is now only five years behind AWS in Azure. Now, our models say, "No way." Google Cloud Platform, by our estimate, is running at about $3 billion per quarter or more like 60% of Google's reported overall cloud revenue. You have to go back to 2016 to find AWS running at that level and 2018 for Azure. So we would estimate that GCP is six years behind AWS and four years behind Azure from a revenue performance standpoint. Now, tech-wise, you can make a stronger case for Google. They have really strong tech. But revenue is, in our view, a really good indicator. Now, we circle here ServiceNow because they have become a generational company and impressively remain above the 40% line. We were at CrowdStrike with theCUBE two weeks ago, and we saw firsthand what we see as another generational company in the making. And you can see the company spending momentum is quite impressive. Now, HashiCorp and Snowflake have now surpassed Kubernetes to claim the top net score spots. Now, we know Kubernetes isn't a company, but ETR tracks it as though it were just for context. And we've highlighted Databricks as well, showing momentum, but it doesn't have the market presence of Snowflake. And there are a number of other players in the green: Pure Storage, Workday, Elastic, JFrog, Datadog, Palo Alto, Zscaler, CyberArk, Fortinet. Those last ones are in security, but again, they're all off their recent highs of 2021 and early 2022. Now, speaking of AWS, Snowflake, and Databricks, our colleague Eric Bradley of ETR recently held an in-depth interview with a senior executive at a large financial institution to dig into the analytics space. And there were some interesting takeaways that we'd like to share. The first is a discussion about whether or not AWS can usurp Snowflake as the top dog in analytics. I'll let you read this at your at your leisure, but I'll pull out some call-outs as indicated by the red lines. This individual's take was quite interesting. Note the comment that quote, this is my area of expertise. This person cited AWS's numerous databases as problematic, but Redshift was cited as the closest competitors to Snowflake. This individual also called out Snowflake's current cross-cloud Advantage, what we sometimes call supercloud, as well as the value add in their marketplace as a differentiator. But the point is this person was actually making, the point that this person was actually making is that cloud vendors make a lot of money from Snowflake. AWS, for example, see Snowflake as much more of a partner than a competitor. And as we've reported, Snowflake drives a lot of EC2 and storage revenue for AWS. Now, as well, this doesn't mean AWS does not have a strong marketplace. It does. Probably the best in the business, but the point is Snowflake's marketplace is exclusively focused on a data marketplace and the company's challenge or opportunity is to build up that ecosystem and to continue to add partners and create network effects that allow them to create long-term sustainable moat for the company, while at the same time, staying ahead of the competition with innovation. Now, the other comment that caught our attention was Snowflake's differentiators. This individual cited three areas. One, the well-known separation of compute and storage, which, of course, AWS has replicated sort of, maybe not as elegant in the sense that you can reduce the compute load with Redshift, but unlike Snowflake, you can't shut it down. Two, with Snowflake's data sharing capability, which is becoming quite well-known and a key part of its value proposition. And three, its marketplace. And again, key opportunity for Snowflake to build out its ecosystem. Close feature gaps that it's not necessarily going to deliver on its own. And really importantly, create governed and secure data sharing experiences for anyone on the data cloud or across clouds. Now, the last thing this individual addressed in the ETR interview that we'll share is how Databricks and Snowflake are attacking a similar problem, i.e. simplifying data, data sharing, and getting more value from data. The key messages here are there's overlap with these two platforms, but Databricks appeals to a more techy crowd. You open a notebook, when you're working with Databricks, you're more likely to be a data scientist, whereas with Snowflake, you're more likely to be aligned with the lines of business within sometimes an industry emphasis. We've talked about this quite often on "Breaking Analysis." Snowflake is moving into the data science arena from its data warehouse strength, and Databricks is moving into analytics and the world of SQL from its AI/ML position of strength, and both companies are doing well, although Snowflake was able to get to the public markets at IPO, Databricks has not. Now, even though Snowflake is on the quarterly shock clock as we saw earlier, it has a larger presence in the market. That's at least partly due to the tailwind of an IPO, and, of course, a stronger go-to market posture. Okay, so we wanted to share some of that with you, and I realize it's a bit of a tangent, but it's good stuff from a qualitative practitioner perspective. All right, let's close with some final thoughts. Look forward a little bit. Things in the short-term are really hard to predict. We've seen these oversold rallies peter out for the last couple of months because the world is such a mess right now, and it's really difficult to reconcile these counterveiling trends. Nothing seems to be working from a public policy perspective. Now, we know tech spending is softening, but let's not forget it, five to 6% growth. It's at or above historical norms, but there's no question the trend line is down. That said, there are certain growth companies, several mentioned in this episode, that are modern and vying to be generational platforms. They're well-positioned, financially sound, disciplined, with strong cash positions, with inherent profitability. What I mean by that is they can dial down growth if they wanted to, dial up EBIT, but being a growth company today is not what it was a year ago. Because of rising rates, the discounted cash flows are just less attractive. So earnings estimates, along with revenue multiples on these growth companies, are reverting toward the mean. However, companies like Snowflake, and CrowdStrike, and some others are able to still command a relative premium because of their execution and continued momentum. Others, as we reported last week, like UiPath for example, despite really strong momentum and customer spending, have had execution challenges. Okta is another example of a company with strong spending momentum, but is absorbing off zero for example. And as a result, they're getting hit harder from evaluation standpoint. The bottom line is sellers are still firmly in control, the bulls have been humbled, and the traders aren't buying growth tech or much tech at all right now. But long-term investors are looking for entry points because these generational companies are going to be worth significantly more five to 10 years down the line. Okay, that's it for today. Thanks for watching this "Breaking Analysis" episode. Thanks to Alex Myerson and Ken Schiffman on production. And Alex manages our podcast as well. Kristen Martin and Cheryl Knight. They help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE do some wonderful editing for us, so thank you. Thank you all. Remember that all these episodes are available as podcast wherever you listen. All you do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante@siliconangle.com, or DM me @dvellante, or comment on my LinkedIn post. And please check out etr.ai for the very 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." (gentle music)

>>Hello, welcome back to the cubes coverage of Monaco, crypto summit presented by digital bits. It's a conference where a lot of the people using digital bits and the industry coming together around the future of crypto in the applicates got a great guest garage, rod cot, founder, and CEO of an innovative company. Love this co I love this company, Luke mogul, Rob, thanks for coming on the queue. Appreciate it. Oh, >>Thank you for having >>Us. Yeah. So I checked out what you guys are doing. You've got the sports metaverse angle going on with super valuable, cuz sports is super entertaining. Uh, people are engaged. There's huge fan base, huge online now, digital convergence going on with the physical, you know, you see all kinds of sports betting going on now everything's going digital. There's a whole nother consumer experience going on with sports and the game is still the same on the, on the field or so to, or the court. That's correct. Yeah. Now it's going to digital take a minute to explain what you guys are working on. >>Yeah, so yes, we are building out a sports ERs where we are bringing athletes, whether they're NBA stars, NFL stars, w N B a many of those athletes into meows giving them the ownership of the entire, um, meows commerce along with gameplay. So that's something from our perspective, this, uh, this is something that we're focused on. We're building out stadiums. Athletes can own stadiums. Athlete can create their own training centers, media hubs. Um, and imagine Lisa, Leslie for example, is building out a woman leadership sports academy, right? We have Michael Cooper building out defensive academy. So those are all the brands. We have 174 NBA w N B stars. And, um, and we are building out this, >>The brand is the brand, is the platform that's correct. That's the trend we're seeing. And it's, it's also an extension of their reach in community. So there's, they can convert their star power and athlete with owner's approval. If they probably write it on to the contracts, he, they can imagine all the complications, but they bring that online and extend that energy and brand equity yep. To fans and social network. Yeah. >>And many of these athletes are tremendous successful in their web two careers, right? Yeah. Um, some are current athletes, some are former athletes, but they have built such a brand persona where people are following them on Instagram. For example, Carlos Boozer. He has like almost 6 million followers between Twitter and Instagram and those kind of brands are looking or how do I give back to the community? How do I engage with my community and web three? And especially with our platform, we are giving that power back to the players. >>So you guys got some big names booers on there. You mentioned Carlos Boozer. You mentioned that Lisa, Leslie others among others, Michael Cooper throw back to the old Lakers, uh, magic. Johnson's kind actually here in crypto. We just saw him in the lobbies and in dinner and the other night, um, at Nobu, um, you got a lot of NBA support. Take a take, take, even explain how you're working this angle. Uh, you got some great traction, uh, momentum. Um, you got great pedigree, riot games in your career. Uh, you kind of get the world, the tech world, the media world, as it comes together. What's the secret sauce here? Is it the NBA relationship combination of the team explained >>It's really focusing on what, uh, we are building on me was focusing on players first, right? So players are literally, we call our platform as, uh, owned by the players, made for the players. Uh, and engagement is really all done through the players, right? So that's our key sauce. And when we worked out with NBA, we, we are part of the NBA BPA acceleration program for 2022 that is funded by a six Z, uh, and, and many others. Um, and our partnership with league is very critical. So it's not only partnered with player association partnered with leagues, whether it's NBA, w N B a NFL. So those are the venues. And this becomes almost a program, especially for athletes to really generate this lifetime engagement and royalty model because some of this famous athletes really want to give back to the communities. So like for example, I use Lisa Leslie a lot, but Lisa, Leslie really wants to empower women leadership, leadership, and really help, um, women in sports, for example. Right? So those are the angles that, um, that really people are excited about. >>Well, for the people watching that might not understand some of the ins and outs of sports and, and rod, your background in your team, it's interesting. The sports teams have been on the big day to train for many, many years. You look at all the stadiums. Now they've got mobile devices, they got wifi under the chairs. They use data and technology to manage the team. Mm-hmm, <affirmative> manage the stadium and venue and operations suppliers, whatnot. And then also the fans. So you, they, they got about a decade or so experience already in the digital world. This is not new to the, to the sports world. Yeah. So you guys come to the table kind of at a good time. >>Yeah. Especially the defi of the sports, right? So there's a defi of the finance, but this is the really, uh, a, a decentralization of the sports is something that there's a lot of traction. And there are many companies that are really focusing on that. Our focus obviously is players first, right? How do we give power to the players? Uh, and those are really driving the entire engagement. And also the brands >>How's the NBA feel about this because, you know, you got the NBA and you get the team, you got the owners. I mean, the democratization of the players, which I love by the way that angle kind of brings their power. Now's the new kind of balance of power. How is the NBA handling this? What's some of the conversations you've had with the, the organization. >>Yeah. So obviously there are a lot of things that, uh, people have to be careful about, right? They have existing contracts, existing, digital media rights. Um, so that's something that, uh, we have to be very tactful when we are working with NBA and NPA, uh, on what we can say, we cannot say. So that is obviously they have a lot of existing multimillion or billion dollar contracts that they cannot void with the web because the evolution of web three, >>You know, I love, uh, riffing on the notion of contract compliance when there's major structural change happening. Remember back in baseball, back in the days before the internet, the franchise rights was geographic territory. Mm-hmm <affirmative> well, if you're the New York Yankees, you're doing great. If you're Milwaukee, you're not doing too good, but then comes the internet. That's good. That's no geography. There's no boundaries. That's good. So you're gonna have stadiums have virtual Bo. So again, how do they keep up with the contracts? Yeah. I mean, this is gonna be a fundamental issue. >>That's >>Good. Good. And I think if they don't move, the players are gonna fill that void. >>That's correct. Yeah. And especially with this, this an IL deal, right. That happened for the players, uh, especially college athletes. So we are in process of onboarding 1.5 million college athletes. Uh, and those athletes are looking for not only paying for the tuition for the colleges, but also for engagement and generating this early on, uh, >>More okay. Rod, we're gonna make a prediction here in the cube, 20, 20 we're in Monaco, all the NBA, NHL, the teams they're gonna be run by player Dows. Yeah. What do you think? A very good prediction. Yeah. Very good prediction. Yeah. I mean you, I mean, that's a joke, I'm joking aside. I mean, it's kind of connecting the dots, but you know, whether that happens or not, what this means is if this continues to go down this road, that's correct. Get the players collectively could come together. Yeah. And flip the script. >>Yeah. And that's the entire decentralization, right. So it's like the web three has really disrupted this industry as you know. Um, and, and I know your community knows that too. >>Of course, course we do. We love it. >>Something from sports perspective, we are very excited. >>Well, I love it. Love talking. Let's get to the, to the weeds here on the product, under the hood, tell about the roadmap, obviously NFTs are involved. That's kind of sexy right now. I get the digital asset model on there. Uh, but there's a lot more under the coverage. You gotta have a platform, you gotta have the big data and then ultimately align into connecting other systems together. How do you view the tech roadmap and the product roadmap? What's your vision? >>Yeah. So the, the one thing that you had to be T full, uh, as a company, whether it's LUT, mogul or any other startup, is you have to be really part of the ecosystem. So the reason why we are here at Monaco is that we obviously are looking at partnership with digital bits, um, and those kind of partnership, whether it's fourth centric, centric are very critical for the ecosystem in the community to grow. Um, and that's one thing you cannot build a, another, uh, isolated metaverse right? So that's one thing. Many companies have done it, but obviously not. >>It's a wall garden doesn't work. >>Exactly. So you have to be more open platform. So one things that we did early on in our platform, we have open APIs and SDKs where not only you as an athlete can bring in your, uh, other eCommerce or web, uh, NFTs or anything you want, but you can also bring in other real estate properties. So when we are building out this metaverse, you start with real estate, then you build out obviously stadiums and arenas and academies training academies, but then athletes can bring their, uh, web commerce, right. Where it's NFT wearables shoe line. So >>Not an ecosystem on top of Luke Mo. So you're like, I'm almost like you think about a platform as a service and a cloud computing paradigm. Yeah. Look different, not decentralized, but similarly enabling others, do the heavy lifting on their behalf. Yeah. Is that right? >>So that's correct. Yes. So we are calling ourself as the sports platform as a service, right. So we want to add the word sports because we, uh, in, in many contexts, right. When you're building metaverse, you can get distracted with them, especially we are in Los Angeles. Right. >>Can I get a luxury box for the cube and some of the metaverse islands and the stadiums you're doing? >>We, we are working >>On it. We're >>Definitely working on, especially the, uh, Los Angeles, uh, stadium. Yeah. >>Well, we're looking for some hosts, anyone out there looking for some hosts, uh, for the metaverse bring your avatar. You can host the cube, bro. Thanks for coming on the cube. Really appreciate. What's the, what's next for you guys, obviously, continuing to build momentum. You got your playful, how many people on the team what's going on, give a plug for the company. What are you looking for share with the audience, some of the, some of your goals. Yeah. >>So, uh, the main thing we're looking for is really, um, from a brand perspective, if you are looking at buying properties, this would be an amazing time to buy virtual sports stadium. Um, so we are, obviously we have 175 stadiums in roadmap right now. We started with Los Angeles. Then we are in San Francisco, New York, Qatar, Dubai. So all those sports stadiums, whether they're basketball, football, soccer are all the properties. And, uh, from a community perspective, if you want to get an early access, we are all about giving back to the community. Uh, so you can buy it at a much better presale price right now. Uh, so that's one, the second thing is that if you have any innovative ideas or a player that you want to integrate into, we have an very open platform from a community engagement perspective. If you have something unique from a land sale perspective yeah. Or the NFD perspective plug, contact us at, at Raj lumo.com. >>And I'm assuming virtual team, you in LA area where where's your home. >>So, yeah, so I live in Malibu, um, and our office is in Santa Monica. We have an office in India. Uh, we have few developers also in Europe. So, uh, and then we are team of 34 people right now >>Looking to hire some folks >>We are looking for, what >>Are you, what are you looking for? >>So, uh, we are looking for a passionate sports, uh, fanatics. >>It's a lot, not hard to find. Yeah. >><laugh> who knows how to also code. Right? So from blockchain perspective, we are, uh, chain agnostic. Uh, but obviously right now we are building on polygon, but we are chain agnostic. So if you have any blockchain development experience, uh, that's something we, we are looking for. Yeah. >>RA, thanks for coming out. Luke Mo check him out. I'm John furry with the cube here in Monaco for the mono crypto summit presented by digital bits. We got all the action, a lot of great guests going on, stay with us for more coverage. Um, John furrier, thanks for watching.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Cube's coverage. We're wrapping up day two, John furrier and Dave ante. We got some friends and colleagues, longtime friends, Crawford Del Pret is the president of IDC. Matt Eastwood is the senior vice president of infrastructure and cloud guys. Thanks for coming on spending time. Great to you guys. >>That's fun to do it. Awesome. >>Cravin I want to ask you, I, I think this correct me if I'm wrong, but this was your first physical directions as, as president. Is that true or did you do one in 2019? >>Uh, no, we did one in 20. We did, we did one in 20. I was president at the time and then, and then everything started, >>Well, how was directions this year? You must have been stoked to get back together. Yeah, >>It was great. I mean, it was actually pretty emotional, you know, it's, it's a community, right? I mean, we have a lot of customers that have been coming to that event for a long, long time and to stand up on the stage and look out and see people, you know, getting a little bit emotional and a lot of hugs and a lot of bringing people together. And this year in Boston, we were the first event really of any size that kind of came back. And when I kind of didn't see that coming in terms of how people, how ready people were to be together. Cause >>When did you did it April >>In Boston? Yeah, we did it March in March. Yeah, it was, it was, it was, it was a game day decision. I mean, we were, we had negotiated it, we were going back and forth and then I kind of made the call at the last minute, say, let's go and do it. And in Santa Clara, I felt like we were kind of opening up the crypt at the convention center. I mean, all the production people said, you know what? You guys were really the first event to be back. And attendance was really strong. You know, we, we, we got over a thousand. It was, it was really good. >>Good. It's always a fun when I was there. It was, it's a big deal. You guys prepare for it. Yeah. Some new faces up on the stage. Yeah. So, so Matt, um, you've been doing the circuit. I take it like, like all top analysts, super busy. Right. This is kind of end of the spring. I mean, I know it's summer, right. That's right. But, um, how do you look at, at discover relative some, some of the other events you've been at? >>So I think if you go back to what Crawford was just talking about our event in March, I mean, March was sort of the, the reopening and there was, I think people just felt so happy to be, to be back out there. You still get a little bit at, at these events. I mean, cuz for each, each company it's their first time back at it, but I think we're starting to get down what these events are gonna feel like going forward. Um, and it, I mean, there's good energy here. There's been a good attendance. I think the, the interest in getting back live and having face to face meetings is clearly strong. >>Yeah. I mean, this definitely shows that hybrids, the steady state, both events cloud. Yeah. Virtualization remotes. So what are you guys seeing with that hybrid mode? Just from a workforce, certainly people excited to get back together, but it's gonna continue. You're starting to see that digital piece. How is that impacting some of the, some of the customers you're tracking, who's winning and who's losing, coming out of the pandemic. What's the big picture look like? >>Yeah. I mean, if you, if you take a look at hybrid work, um, people are testing many, many, many different models. And I think as we move from a pandemic to an em, we're gonna have just waves and waves and waves of people needing that flexibility for a lot of different reasons, whether they have, uh, you know, preexisting conditions, whether they're just not comfortable, whether they have people who can't be vaccinated at home. So I think we're gonna be in this hybrid work for a long, long time. I do think though that we are gonna transition back into some kind of a normal, um, and I, and I think the big difference is that I think leaders back in the day, a long time ago, when people weren't coming into work, it was kind of like, oh, I know nothing's going on there. People aren't getting worked. And I think we're over that stage. Yeah. I think we're now into a stage where we know people can be productive. We know people can effectively work from home and now we're into the reason to be in the office. And the reason to be in the office is that collaboration, it's that mentoring it's that, you know, think about your 25 year old self. Do you wanna be staring at a windshield all day long and not kind of building those relationships? People want face to face, it's difficult. They want face >>To face and I would, and you guys had a great culture and it's a young culture. How are you handling it as an executive in terms of, is there a policy for hybrid or >>Yeah, so, so, so at IDC, what we did is we're in a pilot period and we've kind of said that the summertime is gonna be a pilot period and we've asked people, we're actually serving shocker, we're >>Serving, >>But we're, but we're, but, but we're actually asking people to work with their manager on what works for them. And then we'll come up with, you know, whether you are in, out of the office worker, which will be less than two days a hybrid worker, which will be three days or, uh, in, in the office, which is more than three days a week. And you know, we all know there's, there's, there's limitation, there's, there's, there's variability in that, but that's kind of what we're shooting for. And we'd like to be able to have that in place in the fall. >>Are you pretty much there? >>Yeah, I am. I, I am there three days a week. I I, Mondays and Fridays, unless, >>Because you got the CEO radius, right? Yeah. >><laugh>, <laugh> >>The same way I'm in the office, the smaller, smaller office. But so, uh, let's talk a little bit about the, the numbers we were chatting earlier, trying to squint through you guys are, you know, obviously the gold standard for what the market does, what happened in, you know, during the pandemic, what happened in 2021 and what do you expect to happen in, in 2022 in terms of it spending growth? >>Yeah. So this is, this is a crazy time, right? We've never seen this. You and I have a long history of, uh, of tracking this. So we saw in, in, in, in 2020, the market decelerated dramatically, um, the GDP went down to a negative like it always does in these cases, it was, you know, probably negative six in that, in that, in that kind of range for the first time, since I've been tracking it, which goes back over 30 years, tech didn't go negative tech went to about just under 3%. And then as we went to 2021, we saw, you know, everything kind of snap back, we saw tech go up to about 11% growth. And then of course we saw, you know, GDP come back to about a 4%, you know, ki kind of range growth. Now what's I think the story there is that companies and you saw this anecdotally everywhere companies leaned into tech, uh, company. >>You know, I think, you know, Matt, you have a great statistic that, you know, 80% of companies used COVID as their point to pivot into digital transformation, right. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers now. So this year what's fascinating is we're looking at two Fastly different markets. We've got gasoline at $7 a gallon. We've got that affecting food prices. Uh, interesting fun fact recently it now costs over $1,000 to fill an 18 Wheeler. All right. Based on, I mean this just kind of can't continue. So you think about it, don't put the boat >>In the wall. Yeah. Yeah. >>Good, good, good, good luck. It's good. Yeah, exactly. <laugh> so a family has kind of this bag of money, right? And that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more gadgets and consumer tech are not, you know, you're gonna use that iPhone a little longer. You're gonna use that Android phone a little longer. You're gonna use that TV a little longer. So consumer tech is getting crushed, you know, really it's very, very, and you saw it immediately and ad spending, you've seen it in meta. You've seen it in Facebook. Consumer tech is doing very, very it's tough enterprise tech. We haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be, uh, servers, whether that be, uh, commercial PCs, as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. Um, we have combined that with a component shortage and you're seeing some enterprise companies with a quarter of backlog. I mean, that's, you know, really unheard at higher >>Prices, which >>Also, and therefore that drives that >>Drives. It shouldn't be that way. If there's a shortage of chips, it shouldn't be that way, >>But it is, but it is, but it is. And then you look at software and we saw this, you know, we've seen this in previous cycles, but we really saw it in the COVID downturn where, uh, in software, the stickiness of SaaS means that you just, you're not gonna take that stuff out. So the, the second half of last year we saw double digit rates in software surprise. We're seeing high single digit revenue growth in software now, so that we think is gonna sustain, which means that overall it demand. We expect to be between five and 6% this year. Okay, fine. We have a war going on. We have, you know, potentially, uh, a recession. We think if we do, it'll be with a lower case, R maybe you see a banded down to maybe 4% growth, but it's gonna grow this. >>Is it, is it both the structural change of the disruption of COVID plus the digital transformation yeah. Together? Or is it, >>I, I think you make a great point. Um, I, I, I think that we are entering a new era for tech. I think that, you know, Andrew's famous wall street journal oped 10 years ago, software is even world was absolutely correct. And now we're finding that software is, is eing into every nook and cranny people have to invest. They, they know disruptors are coming around every single corner. And if I'm not leaning into digital transformation, I'm dead. So >>The number of players in tech is, is growing, >>Cuz there's well, the number of players in tech number >>Industry's coming >>In. Yeah. The industry's coming in. So I think the interesting dynamic you're gonna see there is now we have high interest rates. Yeah. Which means that the price of funding these companies and buying them and putting data on is gonna get higher and higher, which means that I think you could, you could see another wave of consolidation. Mm-hmm <affirmative> because tech large install based tech companies are saying, oh, you know what? I like that now >>4 0 9 S are being reset too. That's another point. >>Yeah. I mean, so if you think about this, this transformation, right. So it's all about apps, absent data and differentiating and absent data. What the, the big winner the last couple years was cloud. And I would just say that if this is the first potential recession that we're talking about, where the cloud service providers. So I think a cloud as an operating model, not necessarily a destination, but for these cloud service providers, they've actually never experienced a slowdown. So how, and, and if you think about the numbers, 30% of, of the typical it budget is now quote, unquote cloud and 30% of all expenditures are it related. So there's a lot of exposure there. And I think you're gonna see a lot of, a lot of focus on how we can rationalize some of those investments. >>Well, that's a great point. I want to just double click on that. So yeah, the cloud did well during the pandemic. We saw that with SAS, have you guys tracked like the Tams of what got pulled forward? So the bit, a big discussion about something that pulled forward because of the pandemic, um, like zoom, for instance, obviously everyone's using zoom. Yeah, yeah, yeah. Was there fake Tams? There was one, uh, couple analysts who were pointing out that some companies were hot during the pandemic will go away that that Tam doesn't really exist, but there's some that got pulled forward early. That's where the growth is. So is there a, is there a line between the, I call fake Tam or pulled forward TA that was only for the pandemic situationally, um, devices might be like virtual event, virtual event. Software was one, I know Hoppin got laid a lot of layoffs. And so that was kind of gone coming, coming and going. And you got SAS which got pulled forward. Yep. And it's not going away, but it's >>Sustaining. Yeah. Yeah. But it's, but, but it's sustaining, um, you know, I definitely think there was a, there was a lot of spending that absolutely got pulled forward. And I think it's really about CEO's ability to control expectations and to kind of message what it, what it looks like. Um, you know, I think I look, I, I, I think virtual event platforms probably have a role. I think you can, you can definitely, you know, raise your margins in the event, business, significantly using those platforms. There's a role for them. But if you were out there thinking that this thing was gonna continue, then you know, that that was unrealistic, you know, Dave, to, to your point on devices, I'm not necessarily, you know. Sure. I think, I think we definitely got ahead of our expectations and things like consumer PCs, those things will go back to historical growth >>Rates. Yeah. I mean, you got the install base is pretty young right now, but I think the one way to look at it too, is there was some technical debt brought in because people didn't necessarily expect that we'd be moving to a permanent hybrid state two years ago. So now we have to actually invest on both. We have to make, create a little bit more permanency around the hybrid world. And then also like Crawford's talking about the permanency of, of having an office and having people work in, in multiple modes. Yeah. It actually requires investment in both the office. And >>Also, so you're saying operationally, you gotta run the company and do the digital transformation to level up the hybrid. >>Yeah. Yeah. Just the way people work. Right. So, so, you know, you basically have to, I mean, even for like us internally, Crawford was saying, we're experimenting with what works for us. My team before the pandemic was like one third virtual. Now it's two third virtual, which means that all of our internal meetings are gonna be on, on teams or zoom. Right. Yeah. They're not gonna necessarily be, Hey, just coming to the office today, cuz two thirds of people aren't in the Boston area. >>Right. Matt, you said if you see cloud as an operating model, not necessarily a place. I remember when you were out, I was in the, on the, on the, on the zoom when, when first met Adam Celski yeah. Um, he said, you were asking him about, you know, the, the on-prem guys and he's like, nah, it's not cloud. And he kind of was very dismissive of it. Yeah. Yeah. I wanna get your take on, you know, what we're seeing with as Azure service GreenLake, apex, Cisco's got their version. IBM. Fewer is doing it. Is that cloud. >>I think if it's, I, I don't think all of it is by default. I think it is. If I actually think what HPE is doing is cloud, because it's really about how you present the services and how you allow customers to engage with the platform. So they're actually creating a cloud model. I think a lot of people get lost in the transition from, you know, CapEx to OPEX and the financing element of this. But the reality is what HPE is doing and they're sort of setting the standard. I think for the industry here is actually setting up what I would consider a cloud model. >>Well, in the early days of, of GreenLake, for sure it was more of a financial, you >>Know, it was kind of bespoke, right. But now you've got 70 services. And so you can, you can build that out. But >>You know, we were talking to Keith Townsend right after the keynote and we were sort of UN unpacking it a little bit. And I, I asked the question, you know, if you, if you had to pin this in terms of AWS's maturity, where are we? And the consensus was 2014 console filling, is that fair or unfair? >>Oh, that's a good question. I mean, um, I think it's, well, clouds come a long way, right? So it'd be, I, I, I think 20, fourteen's probably a little bit too far back because >>You have more modern tools I Kubernetes is. Yeah. >>And, but you also have, I would say the market still getting to a point of, of, of readiness and in terms of buying this way. So if you think about the HP's kind of strategy around edge, the core platform as a, as a service, you know, we're all big believers in edge and the apps follow the data and the data's being created in new locations and you gotta put the infrastructure there. And for an end user, there's a lot of risk there because they don't know how to actually plan for capacity at the edge. So they're gonna look to offload that, but this is a long term play to actually, uh, build out and deploy at the edge. It's not gonna happen tomorrow. It's a five, 10 year play. >>Yeah. I mean, I like the operating model. I'd agree with you, Matt, that if it's, if it's cloud operations, DevSecOps and all that, all that jazz it's cloud it's cloud operating and, and, and public cloud is a public cloud hyperscaler on premise. And the storage folks were presented. That's a single pane of glass. That's old school concepts, but cloud based. Yep. Shipping hardwares, auto figures. Yeah. That's the kind of consumption they're going for now. I like it. Then I, then they got the partner led thing is the partner piece. How do you guys see that? Because if I'm a partner, there's two things, wait a minute, am I at bottleneck to the direct self-service? Or is that an enabler to get more cash, to make more money? If I'm a partner. Cause you see what Essentia's doing with what they do with Amazon and Deloitte and et C. Yeah. You know, it's interesting, right? Like they've a channel partner, I'm making more cash. >>Yeah. I mean, well, and those channel partners are all in transition too. They're trying to yeah. Right. Figure out. Right, right. Are they, you know, what are their managed services gonna look like? You know, what kind of applications are they gonna stand up? They're they're not gonna just be >>Reselling, bought a big house in a boat. The box is not selling. I wanna ask you guys about growth because you know, the big three cloud, big four growing pick a number, I dunno, 30, 35% revenue big. And like you said, it's 30% of the business now. I think Dell's growing double digits. I don't know how much of that is sustainable. A lot of that is PCs, but still strong growth. Yep. I think Cisco has promised 9% >>In, in that. Right, right. >>About that. Something like that. I think IBM Arvin is at 6%. Yep. And I think HPE has said, Hey, we're gonna do three to 4%. Right. Which is so really sort of lagging and which I think a lot of people in wall street is like, okay, well that's not necessarily so compelling. Right. What does HPE have to do to double that growth? Or even triple that growth. >>Yeah. So they're gonna need, so, so obviously you're right. I mean, being able to show growth is Tanem out to this company getting, you know, more attention, more heat from, from investors. I think that they're rightly pointing to the triple digit growth that they've seen on green lake. I think if you look at the trailing, you know, 12 month bookings, you got over, you know, 7 billion, which means that in a year, you're gonna have a significant portion of the company is as a service. And you're gonna see that revenue that's rat being, you know, recognized over a series of months. So I think that this is sort of the classic SAS trough that we've seen applied to an infrastructure company where you're basically have to kind of be in the desert for a long time. But if they can, I think the most important number for HPE right now is that GreenLake booking snow. >>And if you look at that number and you see that number, you know, rapidly come down, which it hasn't, I mean off a very large number, you're still in triple digits. They will ultimately start to show revenue growth, um, in the business. And I think the one thing people are missing about HPE is there aren't, there are a lot of companies that want to build a platform, but they're small and nobody cares. And nobody let's say they throw a party and nobody comes. HP has such a significant installed base that if they do build a platform, they can attract partners to that platform. What I mean by that is partners that deliver services on GreenLake that they're not delivering. They have the girth to really start to change an industry and change the way stuff is being built. And that's the be they're making. And frankly, they are showing progress in that direction. >>So I buy that. But the one thing that concerns me is they kind of hide the ball on services. Right. And I, and I worry about that is like, is this a services kind of just, you know, same wine, new bottle or, >>Or, yeah. So, so I, I, I would argue that it's not about hiding the ball. It's about eliminating confusion of the marketplace. This is the company that bought EDS only to spin it off <laugh>. Okay. And so you don't wanna have a situation where you're getting back into services. >>Yeah. They're the only one >>They're product, not the only ones who does, I mean, look at the way IBM used to count and still >>I get it. I get it. But I think it's, it's really about clarity of mission. Well, I point next they are in the Ts business, absolutely. Point of it. It's important prop >>Drive for them at the top. Right. The global 50 say there's still a lot of uniqueness in what they want to buy. So there's definitely a lot of bespoke kind of delivery. That's still happening there. The real promise here is when you get into the global 2000 and yeah. And can start them to getting them to consume very standardized offers. And then the margins are, are healthy >>And they got they're what? Below 30, 33, 30 3%. I think 34% last quarter gross margin. Yeah. That that's solid. Just compare that with Dell is, I don't know. They're happy with 20, 21% of correct. You get that, which is, you know, I I'll come back. Go ahead. I want, I wanna ask >>Guys. No, I wanna, I wanna just, he said one thing I like, which was, I think he nailed it. They have such, um, big install base. They have a great channel. They know how to use it. Right. That's a real asset. Yeah. And Microsoft, I remember when their stock was trading at 26 when Baltimore was CEO. Yep. What they did with no, they had office and windows, so a little bit different. Yep. But similar strategy, leverage our install base, bring something up to them. That's what you're kind of connecting the >>Absolutely. You have this velocity, uh, machine with a significant girth that you can now move to a new model. They move that to a new model. To Matt's point. They lead the industry, they change the way large swath the customers buy and you will see it in steady revenue growth over time. Okay. So I just in that, well, >>So your point is the focus and there the right it's the right focus. And I would agree what's >>What's the other move. What's their other move, >>The problem. Triple digit booking growth off a number that gets bigger >>Inspired. Okay. >>Whats what's the scoreboard. Okay. Now they're go at the growth. That's the scoreboard. What are the signals? Are you looking at on the scoreboard Crawford and Matt in terms of success? What are the benchmarks? Is it ecosystem growth, number of services, triple growth. Yeah. What's the, what are some of the metrics that you guys are gonna be watching and we should be watching? >>Yeah. I mean, I dunno if >>You wanna jump in, I mean, I think ecosystem's really critical. Yeah. You want to, you want to have well and, and you need to sell both ways like HPE needs to be selling their technology on other cloud providers and vice versa. You need to have the VMs of the world on, you know, offering services on your platform and, and kind of capturing some, some motion off that. I think that's pretty critical. The channel definitely. I mean, you have to help and what you're gonna see happen there is there will be channel partners that succeed in transforming and succeeding and there'll be a lot that go away and that some, some of that's, uh, generational there'll be people that just kind of age outta the system and, and just go home. >>Yeah. Yeah. So I would argue it's, it's, it's, it's gonna be, uh, bookings growth rate. It's gonna be retention rate of the, of, of, of the customers, uh, that they have. And then it's gonna be that, that, um, you know, ultimately you're gonna see revenue, um, growth, and which is that revenue growth is gonna have to be correlated to the booking's growth for green lake cross. >>What's the Achilles heel on, on HPE. If you had to do the SWAT, what's the, what's the w for HPE that they really need to pay >>Attention to. I mean, they, they need to continue their relentless focus on cost, particularly in the, in the core compute, you know, segment they need to be, they need to be able to be as cost effective as possible while the higher profit dollars associated with GreenLake and other services come in and then increase the overall operating margin and gross margin >>Picture for the, I mean, I think the biggest thing is they just have, they have to continue the motion that they've been on. Right. And they've been consistent about that. Mm-hmm, <affirmative> what you see where others have, have kind of slipped up is when you go to, to customers and you present the, the OPEX as a service and the traditional CapEx side by side, and the customers put in this position of trying to detangle what's in that OPEX service, you don't wanna do that obviously. And, and HP has not done that, but we've seen others kind of slip up. And, but >>A lot of companies still wanna buy CapEx. Right. Absolutely liquid. And, and I think, >>But you shouldn't do a, you shouldn't do that bake off by putting those two offers out. You should basically ascertain what they want to do. >>What's kind of what Dell does. Right. Hey, how, what do you want? We got this, we got >>This on one hand, we got this, the, we got that, right. Uh, the two hand sales rep, no, this CapEx. Thing's interesting. And if you're Amazon and Azure and, and GCP, what are they thinking right now? Cause remember what, four years ago outpost was launched, which essentially hardware. Yeah. This is cloud operating model. Yep. Yeah. They're essentially bringing outpost. This is what they got basically is Amazon and Azure, like, is this ABL on the radar for them? How would you, what, what are they thinking in your mind if we're on, if we're in their office, in their brain trust, are they laughing? Are they like saying, oh, they're scared. Is this real threat >>Opportunity? I, I, I mean, I wouldn't say they're laughing at all. I, I would say they're probably discounting a little bit and saying, okay, fine. You know, that's a strategy that a traditional hardware company is moving to. But I think if you look underneath the covers, you know, two years ago it was, you know, pretty basic stuff they were offering. But now when you start getting into some, you know, HPC is a service, you start getting into data fabric, you start getting into some of the more, um, sophisticated services that they're offering. And, and I think what's interesting about HP. What my, my take is that they're not gonna go after the 250 services the Amazon's offering, they're gonna basically have a portfolio of services that really focus on the core use cases of their infrastructure set. And, and I think one of the danger things, one, one of the, one of the red flags would be, if they start going way up the stack and wanting to offer the entire application stack, that would be like a big flashing warning sign, cuz it's not their sweet spot. It's not, not what they have. >>So machine learning, machine learning and quantum, okay. One you can argue might be up the stack machine learning quantum should be in their wheelhouse. >>I would argue machine learning is not up the stack because what they would focus on is inference. They'd focus on learning. If they came out and said, machine learning all the way up to the, you know, what a, what, what a drug discovery company needs to do. >>So they're bringing it down. >>Yeah. Yeah. Well, no, I think they're focusing on that middle layer, right? That, that, that data layer. And I think that helping companies manage their data make more sense outta their data structure, their data that's core to what they wanna do. >>I, I feel as though what they're doing now is table stakes. Honestly, I do. I do feel like, okay, Hey finally, you know, I say the same thing about apex, you >>Know, we finally got, >>It's like, okay guys, the >>Party. Great. Welcome to the, >>But the one thing I would just say about, about AWS and the other big clouds is whether they might be a little dismissive of what's truly gonna happen at the edge. I think the traditional OEMs that are transforming are really betting on that edge, being a huge play and a huge differentiator for them where the public cloud obviously have their own bets there. But I think they were pretty dismissive initially about how big that went. >>I don't, and I don't think anybody's really figured out the edge yet. >>Well, that's an, it's a battleground. That's what he's saying. I think you're >>Saying, but on the ecosystem, I wanna say up the stack, I think it's the ecosystem. That's gotta fill that out. You gotta see more governance tools and catalogs and AI tools and, and >>It immediately goes more, it goes more vertical when you go edge, you're gonna have different conversations and >>They're >>Lacking. Yeah. And they, but they're in there though. They're in the verticals. HP's in the, yeah, >>For sure. But they gotta build out an ego. Like you walk around here, the data, the number of data companies here. I mean, Starburst is here. I'm actually impressed that Starburst is here. Cause I think they're a forward thinking company. I wanna see that times a hundred. Right. I mean, that's >>You see HP's in all the verticals. That's I think the point here, >>So they should be able to attract that ecosystem and build that, that flywheel that's the, that's the hallmark of a cloud that marketplace. >>Yeah, it is. But I think there's a, again, I go back to, they really gotta stay focused on that infrastructure and data management. Yeah. >>But they'll be focused on that, but, but their ecosystem, >>Their ecosystem will then take it up from there. And I think that's the next stage >>And that ecosystem's gotta include OT players and communications technologies players as well. Right. Because that stuff gets kind of sucked up in that, in that edge play. Do >>You feel like HPE has a, has a leg up on that or like a little, a little bit of a lead or is it pretty much, you know, even raced right now? >>I think they've, I think the big infrastructure companies have all had OEM businesses and they've all played there. It's it's, it's also helping those OT players actually convert their own needs into more of a software play and, and not so much of >>Physical. You've been, you've been following and you guys both have been following HP and HPE for years. They've been on the edge for a long time. I've been focused on this edge. Yeah. Now they might not have the product traction that's right. Or they might not develop as fast, but industrial OT and IOT they've been talking about it, focused on it. I think Amazon was mostly like, okay, we gotta get to the edge and like the enterprise. And, and I think HP's got a leg up in my opinion on that. Well, I question is can they execute? >>Yeah. I mean, PTC was here years ago on stage talking >>About, but I mean, you think about, if you think about the edge, right. I mean, I would argue one of the best acquisitions this company ever did was Aruba. Right. I mean, it basically changed the whole conversation of the edge changed the whole conversation. >>If >>Became GreenLake, it was GreenLake. >>Well, it became a big department. They gave a big, but, but, but I mean, you know, I mean they, they, they went after going selling edge line servers and frankly it's very difficult to gain traction there. Yeah. Aruba, huge area. And I think the March announcement was when they brought Aruba management into. Yeah. Yeah. >>Totally. >>Last question. Love >>That. >>What are you guys saying about the, the Broadcom VMware acquisition? What's the, what are the implications for the ecosystem for companies like HPE and just generally for the it business? >>Yeah. So >>You start. Yeah, sure. I'll start, I'll start there. So look, you know, we've, you know, spent some time, uh, going through it spent some time, you know, speaking, uh, to the, to the, to the folks involved and, and, and I gotta tell you, I think this is a really interesting moment for Broadcom. This is Broadcom's opportunity to basically build a different kind of a conversation with developers to, uh, try to invest in. I mean, just for perspective, right? These numbers may not be exact. And I know a dollar is not a dollar, but in 2001, anybody, remember what HP paid for? Compact >>8,000,000,020, >>So 25 billion, 25 billion. Wow. VMware just got sold for 61 billion. Wow. Okay. Unbill dollars. Okay. That gives you a perspective. No, again, I know a dollar is not a dollar 2000. >>It's still big numbers, >>2022. So having said that, if you just did it to, to, to basically build your DCF model and say, okay, over this amount of time, I'll pay you this. And I'll take the money out of this period of time, which is what people have criticized them for. I think that's a little shortsighted. I, yeah, I think this is Broadcom's opportunity to invest in that product and really try to figure out how to get a seat at the table in software and pivot their company to enterprise software in a different way. They have to prove that they're willing to do that. And then frankly, that they can develop the skills to do that over time. But I do believe this is a, a different, this is a pivot point. This is not >>CA this is not CA >>It's not CA >>In my, in my mind, it can't be CA they would, they would destroy too much. Now you and I, Dave had some, had some conversations on Twitter. I, I don't think it's the step up to them sort of thinking differently about semiconductor, dying, doing some custom semi I, I don't think that's. Yeah. I agree with that. Yeah. I think I, I think this is really about, I got two aspiration for them pivoting the company. They could >>Justify the >>Price to the, getting a seat at the adults table in software is, >>Well, if, if Broadcom has been squeezing their supplies, we all hear the scutle butt. Yeah. If they're squeezing, they can use VMware to justify the prices. Yeah. Maybe use that hostage. And that installed base. That's kind of Mike conspiracy. >>I think they've told us what they're gonna do. >><laugh> I do. >>Maybe it's not like C what's your conspiracy theory like Symantec, but what >>Do you think? Well, I mean, there's still, I mean, so VMware there's really nobody that can do all the things that VMware does say. So really impossible for an enterprise to just rip 'em out. But obviously you can, you can sour people's taste and you can very much influence the direction they head in with the collection of, of providers. One thing, interesting thing here is, was the 37% of VMware's revenues sold through Dell. So there's, there's lots of dependencies. It's not, it's not as simple as I think John, you you're right. You can't just pull the CA playbook out and rerun it here. This is a lot more complex. Yeah. It's a lot more volume of, of, of distribution, but a fair amount of VMware's install >>Base Dell's influence is still there basically >>Is in the mid-market. It's not, it's not something that they're gonna touch directly. >>You think about what VMware did. I mean, they kept adding new businesses, buying new businesses. I mean, is security business gonna stay >>Networking security, I think are interesting. >>Same >>Customers >>Over and over. Haven't done anything. VMware has the same customers. What new >>Customers. So imagine simplifying VMware. Right, right. Becomes a different equation. It's really interesting. And to your point, yeah. I mean, I think Broadcom is, I mean, Tom Crouse knows how to run a business. >>Yeah. He knows how to run a business. He's gonna, I, I think it's gonna be, you know, it's gonna be an efficient business. It's gonna be a well run business, but I think it's a pivot point for >>Broadcom. It's amazing to me, Broadcom sells to HPE. They sell it to Dell and they've got a market cap. That's 10 X, you know? Yes. Yeah. All we gotta go guys. Awesome. Great conversation guys. >>A lot. Thanks for having us on. >>Okay. Listen, uh, day two is a, is a wrap. We'll be here tomorrow, all day. Dave ante, John furrier, Lisa Martin, Lisa. Hope you're feeling okay. We'll see you tomorrow. Thanks for watching the cube, your leader in enterprise tech, live coverage.

>>Welcome back to the cubes, continuous coverage of AWS reinvent 2021. I'm Lisa Martin. We are winning one of the industry's most important in hybrid tech events this year with AWS and its enormous ecosystem of partners to life sets we have going on right now. There's a dueling set right across from me, two remote studios over 100 guests on the program. We'll be digging into really the next decade of cloud innovation. I'm pleased to welcome two guests that sit next to me here. We've got Aaron Arnold Santa's partner at BCG gamma and a diesel associate director of data science at BCG gamma guys. Welcome to the program. Thanks for having us. I D let's go ahead and start with you. Give us the low down what's going on at BCG gamma. >>We are focused on building responsible, sustainable, and efficient AI at scale to solve pressing business problems. >>Good. We're going to dig into that more. There was a lot of talk about AI this morning during the keynote yesterday as well. And you know, one of the things Aaron that we talked about the last day and a half is that every company, these days has to be a data company, but the volume of data is so great that we've got to have AI to be able to help all the humans process it, find all of the nuggets that are buried within these volumes of data for companies to be competitive. You talk about a sustainable efficient let's go ahead and talk about what do you mean by efficient AI? It sounds great, but help unpack what that actually means. And, and how does an organization in any industry actually achieving? >>Yeah. So when we talk about efficient AI, we're really talking about resilience, scale and adoption. So we all know that the environment in which AI tools and systems are deployed change and update very frequently, and those changes and updates can lead to errors, downtime, which erode user trust. And so when you're designing your AI, it's really critical to build it right and, and ensure it's resilient to those types of changes in the operational environment. And that really means designing it upfront to adhere to company standards around documentation, um, testing bias as well as approved model architecture. So, so that piece is really critical. The other piece about efficient AI is we're really talking about using better code structure to ensure that and enable that teams can search learn, um, and really clone AI IP to bring AI at scale across company silos. So what efficient AI does is it ensures that companies can go from proof of concept and exploration to deploying AI at scale. The final piece is really about solving the right business problems quickly in a way that ensures that users and customers will adopt and actually use the tool and capability >>That adoption there is absolutely critical. And >>You know, when we, when we're talking about AI, most of the time we're talking about three components and we call it like the ten twenty, seventy rule, 10% of the change is really about the better AI algorithms that are coming out. 20% is a better architecture, the technology, all of those components, but 70% of it is really about how are we influencing our business partners to make better decisions? How are we making sure AI is built right into the operational decision flow? And that's really, when we start talking about better AI, we move it away from kind of our pet project, buzzword bingo, into decision operational flows, you know, and, and there's, there's a journey there, there's a journey that we all are on. You see the evolution of AI right now. And I th and I liken it a lot to, um, myself when I'm, I'm a big football fan, right. And I've fantasy football is like my passion. I see. And when I look at the decision-makings, I've made 10 years ago versus now, now I actually have my own models. I'm running against it. I'm, I'm very much into the details of what is the data telling me, but, um, it's not until I bring that together with my decision making process, that really makes it so that I have bragging rights on Sundays. >>I wouldn't want to compete against Aaron. I mean, you know, I've got a lot of friends that do fantasy football, but I don't think they're taking, they're actually doing data-driven approaches as you are. One of the things I'm glad that you talked about the 10, 20, 70 formula for in dividing investments in AI. One of the things that really surprised me, and I'm looking at my notes here, because I was writing this down was that you said 10% AI and machine learning algorithms, 20% software and technology infrastructure, 70% though is also change management. That is hard, especially the speed with which every industry is operating today. What we've seen in the last 22 months, we've seen a massive acceleration to the cloud, every business pivoting, many times where our customers, in terms of understanding the challenges that they can solve with AI, given the fact that we're still in such a dynamic global environment, do what are you seeing? >>So I think it's actually quite, bi-modal some companies, including the public sector are really leaning in and exploring all the different applications and all the different solutions. Unfortunately, if they're not emphasizing that 70% on change management and the culture change and user adoption, those are substantial, but you don't get the return on the investment. Right. On the other hand, the other part of that bi-modal distribution is there are folks who are still really reluctant because they have made investments and it hasn't right. Brought about the change that they were hoping for. And so I think it's really critical to bring that holistic approach to bringing AI and advanced analytic tools to really change the way, you know, a company's attacking its problems and bringing solutions to its users and customers. >>Yeah. I like it a lot to us as us, as adults have when we teach our kids about math, right? Like less of my time with my own kids is focused on teaching them, the principles, the, and all those things, but it's more teaching them to be comfortable. Why are they learning math? What are they doing? How is that going to prepare them to be more competitive and, uh, later on in life. And so, and then the same thing's happening in this evolution in AI, right? There is this big tech and AI transformations that are happening. But the questions we need to ask ourselves within is are we taking the time to make sure our companies and our people are on the journey with us and that they understand that this is going to be better for them and give them a competitive advantage. >>That's critical. We know we've talked a lot in Alaska. We talk a lot about every show about people, process technologies and people as part of that. But I've definitely seen more of a focus. I think the last two and a half days of the people emphasis going, we have to have, we have to upskill our people. We have to train our people. We have to make sure that they're understand how this technology can partner with them and enable them rather than take things away. So it's nice to hear you talking about the big focus there being on the people that is because without that, then a deed to your point, a lot of those projects aren't successful >>And not only, I think the other piece there in terms of bringing the user along for the journey is you don't want them to feel like this is just another tool, right? Another part of their, in addition to their workflow, right? You want to take the burden away. You want it to really, um, not add, but to, to their, to their list of, of daily tasks, but subtract and make it easier. Right. And I think that that's really critical for a lot of companies as well. >>I think along with what you're talking about, we have to teach people to be responsible. So it's, it's one thing to do the job better, but it's another thing to be responsible because in today's world, we have to think about our responsibilities back to our communities, to our consumers, to our shareholders and into ultimately to the environment itself. And so responsive as we are thinking about AI, we need to think differently too, because let's face it. Data is fuel and we can accidentally make the wrong decisions for the globe by making the right decisions for stakeholders. We have to do a better job of understanding the why we're doing what we're doing, what we're doing, and not only the, the intended consequences of our decisions, but also the unintended consequences. And then we need to be responsible in the ways that we're using AI and that we're transparent in our use thereof. >>Yeah, Aaron, I think that's incredibly critical. I think responsible AI, um, has to be at the heart of, of AI transformation. And one of the interesting things that we have found is that organizations perceive their responsible AI maturity to be substantially higher than it actually is. Right. And less than 50% of organizations that have, you know, a fully implemented AI at scale, do not have a responsible AI, um, capability. And so at BCG, we've been working quite hard to integrate our gamma responsible AI program into the big AI transformations, because it's so critical. It's so absolutely important. And, and really that there's a lot of facets to that. But one of that, one of the critical ones is an ensures the goals and the outcomes of the AI systems are fair and unbiased and explainable, which is so critical. Um, I think it also ensures best that we follow best practices for data governance to protect user privacy, which I think is another critical, um, piece here, as well as minimizing any negative social or environmental impact, which again, I it's, it's just gotta be at the forefront of AI development. What about, >>And I think that there's a tech part to that too. So like one thing that we're working on called a gamma facet is really, you know, for the longest time in this AI transformation, AI was kind of a black box and it's kind of mystical, but we, we optimize our results. The transformation, when we talk about better, AI is, uh, the decision maker is in the center and knows the outcome. And so we make it a clear box. And so they're really, we're working a lot on, you know, the most common Python packages, uh, to make them more clear too, so that the business user and the data scientist understands the decisions that they're making and how it will impact the company and longer term society. >>What about the sustainability front? I mean, it's clear that I can understand why you have the 10 20, 70 approach that, that 70% is really important. There are companies that think they're much farther advanced in terms of responsible use of responsible AI responsibly than they really are. Um, but you know, we talk about sustainability all the time. It's a buzzword, but it's also something that's incredibly important to you to companies like AWS. I imagined a companies like yourself, where does, what does sustainable AI look like and how to organizations implemented along with responsible AI efficient AI? >>Yeah, I think it's the question in some ways right now, given everything that's happening around the world. And so AI for sustainability is, is really critical. I think we all have a part to play in this fight, um, to ensure our, our global environment. So I think we need to use the same AI expertise, the same AI technology that we bring to maximize revenue and minimize cost, um, to, to minimizing a company's footprint. Long-term I think that's really critical. One of the things we've seen is that 85% of companies want to reduce their emissions, but less than 10% of them know how to accurately measure right. Their footprint. And so we've been focusing on AI for sustainability across a couple of different pillars. The first is measuring the current impact from operations. The second is data mining, um, for optimal decisions to reduce that footprint. And the third is scenarios to plan better strategies to alter our impact. >>Excellent. Well, there's so much work to be done, guys. Thank you for joining me talking about what BCG is doing for responsible, efficient, ethical, and sustainable AI, a lot of opportunities. I'm sure for you guys with AWS and your list of clients, but we thank you for taking the time out to talk with us this morning. So much. I write for my guests. I'm Lisa Martin. You're watching the cube, the global leader in live tech coverage.

(calm electronic music) >> Welcome to this CUBE Conversation with Fortinet. I'm Lisa Martin. John Madison joins me, the CMO and EVP of products. John, welcome back to the program. >> Thanks Lisa. Good to be here. >> Good to see you. So, so much has changed since I last saw you. The move to remote work caused by the pandemic led so many organizations to invest in modern networking and security technologies. And we see, you know, the rise in the threat landscape that protecting digital assets is becoming even more and more urgent because the threats are continuing to escalate. Talk to me about some of the things that you're seeing with this current threat landscape. >> Yeah. Well, it keeps changing that's for sure. You saw some recent surveys where, you know, now companies are seeing, in terms of where employees are located, you know, 25% expecting to be in the office, 25% expected to be permanently in the home. And then there's this big 50% of hybrid, which we think will move a bit more towards the office as people get back in the office. But that's going to take some time. We're actually starting to move back in the office here in Santa Clara, Sunnyvale. but it's very different in every region in the U.S and regulations and laws around the world. And so we think it's going to be very much work from anywhere. There's a bit of travel starting as well. And so this work from anywhere concept is going to be very important to customers going forward. And the ability to change the dynamics of that ratio as they go forward. >> (indistinct) This work from anywhere that over- last year overnight sort of became an absolute essential. But now, as you said, we're going to have this hybrid model of some going back, some staying home and the security and the perimeter is dissolving. When you look at supporting customers and their remote work from anywhere, their new work from anywhere model, what are some of the things that are top of mind that you're hearing from customers? >> Well, I, you know, I sometimes hear this premise is disappearing. I think in some ways it's moving to the user and the devices. And there's this concept called zero trust network access which I've said in many occasions should be zero trust application access, but they named it that way which is going to be an important technology because as I said, it kind of moves that premise then to that user and previous technology that we had VPN technology was good technology. And in fact, a lot of companies, if you go back to when the pandemic started last year, put a lot of people on the VPN technology as quick as possible and it was reasonably robust. But as we go forward, what we're going to have to do is make sure that perimeter- at that perimeter, that users only get access to the applications they're using rather than the whole network. Eventually when they're on the network you need to make sure that it's segmented so they can't go everywhere as well. And so this zero trust network access or zero trust or zero trust access, there's lots of kind of different versions of it, is going to be very important concept for users. The other piece of it, I think, is also that it needs to be more intuitive to use, as anything you kind of have users do like the VPN where you had to kind of dial in and- or bring up- you're bringing up your connection and your IPsec connection, et cetera, et cetera means that people tend not to use it. And so to make it intuitive and automatic is going to be really important. >> Intuitive and automatic. One of the things that we also saw was this massive rise in digital transformation last year, right? SAS adoption, these SAS applications keeping many of us in collaboration. So I'm thinking, you know, in that sense with the perimeter changing and the work from anywhere, this consistent, secure internet connection among users at the branch or the branch of one has to be there to keep organizations productive and safe. How is the Fortinet enabling the ZTNA- this evolution of VPN? >> Yeah. That's another piece of it. So not only are users on and off the network or traveling so that- or both, so the applications are moving. So a lot of them are moved from data centers to public cloud in the form of infrastructure or SAS. We're now seeing customers actually move some applications towards the building or building compute or edge compute. So the applications keep moving which also causes this problem. And so another function of zero trust access or ZTNA is to not care where the application is. You rely on some technology and it's called proxy technology, which allows the proxy to track where the applications are. And for us, that sits inside of our firewalls. And that makes it very flexible. And so we've been able to kind of just ramp up that proxy against the policy engine, whether it be in the data center or in the cloud, or even on your premise. Even integrated inside a branch or something like that. That's going to be very important because, as you just said, those applications will just keep moving into different areas and different zones as you go forward. >> (Lisa) And that's probably going to be permanent for a lot of organizations. So it- so they haven't renamed it zero trust application access, like you think it should be. But when organizations are looking into zero trust network access, what should- what are some of the key things that they need to be looking for and mindful of? >> Yeah, (indistinct) And so it's probably the, you know, the number one conversation they've had over the last six months. I think people initially just had to get something working. Now they're looking seriously at a longer term architecture for their access, their user access and device access. I think what I find is that something like zero trust network access is more of a use case across multiple components. And so if you look inside it, you need a client component endpoint; you need a proxy that in front of the cloud capabilities; you need a policy engine; you need to use identity-based systems. If you haven't got- if you can't get an agent on the device, you may need a NAC system. And so usually what customers find is I've got four or five current- different vendors in those areas. And cybersecurity vendors are not the best at working together, which they were, because then we do better for customers. And so trying to get two vendors to work is hard enough, trying to get five or six is really hard. And so what they're looking at over time is to say, maybe I get the minimum basic ZTNA working. And then as I go forward, for example, what they really want is this continuing posture assessment. Well, you can do that with some EDR technology, but is that EDR technology integrated into your policy engine? No. So I think what customers are saying is, let me start with the base ZTNA with maybe two vendors. And then as I go forward implement a, you know, a fabric or a platform approach to get everything working together. 'Cause it's just too hard with five or six vendors. >> Right. Is there, I'm curious if there's a shared responsibility model with customers working with different vendors; what actions and security responsibilities fall on the customer that they need to be aware of? >> Well, and it also comes back to this, you know, there's convergence of networking and security. And I've said a few times I'm definitely seeing CIOs and CSOs, security teams, and networking teams working much more closely. And especially when you've got a use case now that goes across security items and networking items and networking, the proxy has always been in the control of the networking team. Endpoint security is always been in the- you know, the security team. It's just forcing this convergence not just of the technologies itself but of the organizations inside enterprises. >> (Lisa) Well, and that's a challenging one for every organization is getting, you know, if you're talking about it in general, the business folks, the IT folks. Now this is not just a security problem. This is a problem for the entire corporation, as we just saw with the Colonial Pipeline. Ransomware is now becoming a household name. These are business-critical board-level discussions I imagine on the security side. How is Fortinet helping customers kind of bridge that gap between the biz folks and the IT folks where security is concerned? >> Yeah. You know, ransomware has been around quite a while. I think two years ago, we saw a lot of it in the schools. K-12 schools in the U.S. I think they're picking some richer targets now. The colonial one, I think there was a 4 million ransom. I think that they managed to get some of that money back. But, you know, instead of, you know, demanding $5,000 or $10,000 from a small business or a school they're obviously demanding millions from these larger companies. And you know, one of the problems with ransomware is, you know, it still relies heavily on social engineering. I don't think you can eliminate that people clicking on stuff, you know, a very small percentage still. I think what it means is you have to put some more proactive things in place, like the zero trust, like micro-segmentation, like web application file warning. All these capabilities to try and make your systems as strong as possible. So then put in detection and response systems to assume that someone's clicking on something somewhere just to help. But it's definitely the environment. You know, the threat environment. It's not really gotten more sophisticated; yes, there are still advanced threats. I fear more about those weaponized APTs and state sponsored, but there's definitely a huge volume of ransomware now going after, you know, not only, you know, meat processing factories, but pipelines and critical infrastructure as we go forward. That's the more worrying. >> (Lisa) Right. You bring up a good point about, sort of, people being one of the biggest challenges from a security perspective. Clicking on links, not checking to see if a link is bogus or legitimate. So, help me understand a little bit more how is zero trust can help maybe take some of that human error out of the equation? >> Well, because I think before, you know, when you got access, when you're off the network and you've got access to the network, you've got access to everything, okay. So once you're on the network, and I think the Colonial Pipeline was a good example where traditionally, operational technology networks, physical networks sort of separate from the IT network and they had something called an air gap. And that air gap meant you really couldn't get to it. Now when people had to be remote because of the pandemic, they started taking these air gaps. And so now we had remote access. And so again, when you- when they got that remote access and they got into the network, they could- the network was very flat and you could see everything you can go anywhere. And so that's what zero trust does. It kind of says, I kind of did the zero trust approach to you that I'm only going to allow you access to this application. And I'm going to keep checking on you to make sure you are you are who you say you are on a continuous basis. And that really provides a bit more safety. Now, I still- we still think you need to put things like segmentation in place and some other capabilities and monitoring everything else, but it just narrows the attack surface down from this giant network approach to a specific application >> Narrowing that is the right direction. How do organizations, when you're working with customers, how do they go- How do they evolve from a traditional VPN to zero trust? What are some of the steps involved in that? >> Well, I think it's, you know, what's interesting is customers still have data centers. In fact, you know, some of the customers who have legacy applications will have a data center for a long time. And in fact, what I find is even if you've implemented zero trust to a certain population, employee population, they still have VPNs in place. And sometimes they use them for the IT folks. Sometimes they use them for a specialized developers and stuff like that. And so I think it's going to be like everything, everything goes a hundred percent this way and it stays this way. And so it's going to be hybrid for a while where we see VPN technology and zero trust together. You know- our approach is that you can have both together and it's both on the same platform and it'll just gradually evolve as you go forward. >> What are some of the things you're looking forward to in the next year as this hybrid environment continues, but hopefully things start to open up more? What are some of the things that we can expect to hear and see from Fortinet? >> Well, I'm looking forward to getting out of my home office, that's for sure. >> (Lisa laughing) >> It's like I've been imprisoned here for eighteen months. >> I agree with you on that! So we'll try that. And, you know, I always thought I traveled too much before and now I'm contemplating on the travel piece. But from, you know, Fortinet's perspective, you know, our goal is to make sure that, you know, our customers can increase. We'll make sure they can protect themselves. And so we want to help them and keep working with them such that they put best practices in place and they start architecting longer-term to implement things like zero trust or sassy or some of these other capabilities. And so, you know, I think the- we've had a lot of interest with customers on these virtual sessions. I'm really looking forward to getting them back in our new building, our new executive briefing center, which we're opening up in the next few weeks. You may have more of those face-to-face and white boarding conversations with customers. >> Oh, that sounds so exciting. I agree with you on the travel front, but going from traveling a ton to none was a big challenge. But also, I imagined it'll be great to actually get to collaborate with customers again, and partners. You know, you can only do so much by Zoom. Talk to me a little bit about some of the things on the partnership front that we might be seeing. >> Yeah, our partners, you know, we're a hundred percent partner-driven company and partners are very important to us. And, you know, and that's why we always, when we introduce new technology, we work with the partners to make sure that they understand it. So for example, we provide free what they call an NSE training to all our partners. And then we also work with them very closely to put systems in their labs and the demos and make sure they can architect. And so partners are really important to us and, you know, making sure that they can provide value as part of a solution set to our customers, because customers trust them. And so we want to make sure that we work with our partners closely so they can help the customer implementing architect solutions as they go forward. >> That trust is critical. Right? I mean, we can talk about that at every event, every CUBE Conversation, the trust that an a customer has in you, the trust that you have in a partner and vice versa. That whole trust circle kind of goes along the lines with what we're talking about in terms of being able to establish that trust. So that threat landscape that's probably only going to continue to get bigger is in the trusted hands of folks like Fortinet and your partners to be able to enable those customers to narrow that threat landscape. >> Yeah, yeah. And so it could be the smallest partner to the largest service provider. We don't mind. We want to make sure that we're working with them to provide that implementation from the customers. And again, the word trust is sometimes overused, but that's what customers are looking for. >> (Lisa) So, John, point me to when our audience is some of the information that they can find on Dotcom about zero trust. What are some of the things that you think are great calls to action for the audience? >> Yeah. I mean, it depends. I think it depends on what level you want to get into where we have a bunch of assets, videos, and training but start at the very highest level, you know, why is zero trust something you need to implement? And then it goes down into more details and then even the architecture, long-term architecture and connectivity and implementation. So there's a lot of assets on Fortinet.com If you go on our training sessions, there's- all our training's free to our customers. And so you can go in all those NSE levels and look at the capabilities. So yeah, definitely it's a- it's an area of high interest from our customers. But as I say to them, it's more of a journey. Yes, you can implement something today really quickly, but will that work for you over the long-term in making sure you can take all the information from the, like I said, you know, how is the voice, the posture of that device? What is the device with an agent doing, you know, as my contextual engine integrated as well? So it's a journey for customers and, but you can start with something simple but you need to have that plan for that journey in place. >> I imagine though, John, it's a journey that is either accelerating, or with the threat landscape and some of the things that we've already talked about, is becoming an absolutely board-critical conversation. So, and on that journey, does Fortinet work with customers to accelerate certain parts of it? Because you know, these businesses have been pivoting so much in the last year and they've got to not just survive, but now thrive in this new landscape, this new hybrid work from home, work from anywhere environment and also with more threats. >> Yeah, no, it's a good point. And so, you know, even those internally are implementing it starting the most critical assets first. So let's say, you know, I've got somebody working on source code, they should be the first ones to get the zero trust implementation. I've got somebody asking from the internet to search for stuff. Maybe they're okay for now, but yeah. So you kind of prioritize your assets and users against, you know, the threat and then implement. That's why I'm saying you can roll it out across everyone as, you know, a certain version of it. But I think it's better to prioritize first the most important assets in IP and then roll it out that way. >> (Lisa) Great advice. >> Because some of- a lot of those assets are still sitting in the data center. >> Right. >> So they're not sitting in the cloud. >> Right. John, great advice. Thank you so much for joining me. Good to see you, glad all is well and that you will be able to get out of your home office. You're just days away from that. I'm sure that's going to feel great. >> Certainly is. And thank you, Lisa. >> Nice to see you. For John Madison, I'm Lisa Martin. You're watching this CUBE Conversation. (calm electronic music with piano)

>>Yeah. Welcome to the cubes coverage for mobile world Congress 2021. I'm john for your host of the cube we're here in person as well as remote. It's a hybrid event were on the ground. Mobile concert green. All the action here were remote with vodka, who is the managing director of the telecom industry solutions team and google cloud, a big leader and driving a lot of the change. Well, thank you for coming on the cube here in the hybrid event from over world Congress. >>Thank you john thank you john thank you for having me. >>So hybrid event which means it's in person were on the floor as well as doing remote interviews and people are virtual. This is the new normal kind of highlights where we are in the telecom world because last time mobile World Congress actually had a physical event was winter of 2019. A ton has changed in the industry. Look at the momentum at the edge. Hybrid cloud is now standard Multi cloud is being set being set up as we speak. This is all now the new normal. What is your take it? It's pretty active in your, in your industry. Tell us your opinion. >>Yes, john, I mean the last two years have been >>seismic to say the >>least, right. I mean, in terms of the change that the CSP industries had had to >>do, you >>know, jOHn uh, in the last two years, the importance of a CSP infrastructure has never become so important, right? The infrastructure is paramount. I'm talking to you remotely over a CSB infrastructure right now and everything that we're doing in the last two years, whether it's working or studying or entertaining ourselves all on that CSP infrastructure. So from that perspective, they are really becoming a critical national, global information fabric on which the society is actually depending >>on and >>That we see at Google as well, in the sense that we have seen up to 60% increase in demand John in the last two years for that infrastructure. And then when I look at the industry itself, unfortunately, all of that huge demand is not translating into revenue because as an industry, the revenue is still flatlining, in fact the forecasted Revenue for globally for all the industry over the next 12 months is 3-5% negative on revenue. Right? So one starts to think how come there is so much demand over the last two years post pandemic and that's not translating to revenue. Having said that, the other thing that's happening is this demand is driving significant Capex and Opec's investments in the infrastructure, as much as 8 to $900 billion over the next decade is going to get spent in this infrastructure from >>our perspective, >>which means it's really a perfect storm, john that we have massive demand, massive need to invest to meet that demand, yet not translating to revenue. And the crux of all this is customer experience because ultimately all of that translates into not having that kind of radically disruptive or transformational customer experience. Right? So that's a backdrop that we find ourselves in the industry and that really sets the stage for us to look at these challenges in terms of how does the CSP industry as a whole growth up line? Radically transformed PST CEO at the same time reinventing the customer experience and finding those capital efficiency, it's almost an impossible problem to solve them. >>It's a perfect storm. The waves are kind of coming together to form one big wave. You mentioned Capex and Opec's that's obviously changing the investments. Are there post pandemic growth and changing the user behavior and expectations. The modern applications are being built on top of the infrastructure. That's changing all of this is being driven by cloud native and that's clear. And you're seeing a lot more open kind of approaches, I T and O. T. Coming together whatever you want to do, this is just it's a collision, right? It's a collision of many things and this positive innovation coming out of. So I have to ask you, what are you seeing the solutions that are showing the most promise for these telco industry leaders because they're digitally transforming so they gotta re factor their platforms while enabling innovation, which is a key growth for the revenue. >>Yes. So john from a solution standpoint, what we actually did first and foremost as google cloud was look at ourselves. So just like the transformation we just talked about in the CSB industry, we are seeing google being transformed over the last two decades or so. Right. And it's important to understand that there's a lot google did over the last two decades that we can actually now externalize all of that innovation, all of that open source, all of that multi cloud was originally built for all the google applications that all of us use daily, whether it's Youtube or mail or maps, you know, same infrastructure, same open source, same multi cloud. And we decided to sort of use the same paradigms to build the telecom solutions that I'm going to talk about next. Right? So that's important to bear in mind that those assets were there and we wanted to externalize those assets right. There are really four big solutions that are resonating really well with our CSP partners, john you know, number one to your point is how can they monitor? Is the edge all of this happens at the edge. All of these kids can watch at the edge we believe with five G acting as a brilliant catalyst to really drive this edge deployment, CSP s would be in a very strong position, partnering with cloud players like ourselves to drive growth, not just for that offline, but also to add value to the actual end enterprises that are seeking to use that age. Let me give you a couple of examples. We've been working with industries like retail and manufacturing to create a solutions in a post pandemic world solutions like contact less shopping or visual inspection of an assembly line in a manufacturing plant without the need for having a human there because of the digitization of workforce, which meant these kind of solutions can actually work well at the edge Driven by 5G, but of course they can't be done in isolation. So what we do is we partner with CSP s, we bring our set of solutions and we actually launched in december 30 partners that already on our google cloud solutions and then we partner with the CSP is based on our infrastructure and their infrastructure to ultimately bring this ball to life at the end customer which opened, tends to be an enterprise, whether it's a manufacturing plant, you >>guys got some great examples there, I love that edge story, I think it's huge and it's only gonna get bigger. I gotta ask you, Well, I got you here because again, you're in the industry the managing director, so you have to oversee this whole telecom industry, but it's bigger. It's beyond telecom right now, telecoms. Just one another. Edge network piece of the pie. And the distributed computing, as we say. So I have to ask you one of the big things that google brings to the table is the developer mojo and open source and scale obviously the scales unprecedented. Everyone knows everyone knows that. Um, but ecosystems are super important and telcos kind of really aren't good at that. So, you know, the telco ecosystem was, I mean, I'd say okay, but mostly driven by carriers and and moving bits from point A to point B. But now you've got a developer mindset, public cloud developer ecosystem. How is this changing the landscape of the CSP and how are they changing how is it changing this cloud service providers ability to execute? Because that's the key in this new world. What's your opinion? >>Absolutely, john So there are two things, there are two dimensions. Look at. One is when we came to market a couple of years ago with anti offs, we recognize exactly what you said, jOHn which is the world is moving to multi cloud hybrid cloud. We needed to provide a common platform that the developer community can utilize through microservices and A P I and that platform had to, by definition work not just from google cloud but any club. It could work on any public cloud can work on CSP s private cloud And of course for >>some google cloud. Right. >>The reason was once you deploy and tossed once as a seamless application development platform, You could put all kinds of developer acts on top. So I just talked about 5GH John a minute ago. Those acts can sit on Santa's but at the same time I did to your point John I thi apps could also sit on the same and toss paradigm and network apps. So as network start becoming cloud native, whether it's ran, whether it's all ran, whether it's five G core same principle and that's why we believe when we partner with the SPS were saying, hey, you give this Antos to an ecosystem of community, whether that community is network with the communities, it with the communities, edge apps, all of those can reside seamlessly on this sort of Antos fabric. >>And that's going to set the table for multi cloud, which is basically cloud words for multi vendor, multi app. Well I got to ask you while you have here, first of all, thank you for coming on and sharing your insights. It's really great industry perspective and it's a google clouds got huge scale, great leadership and again, you know, the big, the big cloud players are moving in and helping out and enabling a lot of value. I gotta ask you if you don't mind sharing. If someone asked you him all, tell me about the uh impact that public cloud is having on the telco industry, what would you say? What's, what's the, what's the answer to that is? A lot of people are like, OK, public cloud, I get it, I know what it looks like, but now everyone knows it's going hybrid. So everyone ask, we'll ask you the question, what is public cloud doing for the telecom sector? >>Yeah, I think it's been treating john and great question by the way. Um number one, we are actually providing unprecedented amount of insight on data that the CSP traditionally already had but have never looked at it from the angle we have looked at whether that insights are at the network layer, whether those insights are to personalize customer experiences on the front end systems or whether those insights are to drive care solutions in contact centers and so on and so forth. So it's a massive uplift of customer experience that we can help, Right? So that's that's a very important point because we do have a significant amount of leadership johN at google cloud and analytics and data and insects. Right? So and we offer goes to overseas people. Number two is really what I talked about which is helping them build an ecosystem because let's take retail as an example as a minimum. There are five constituents in that ecosystem, jOHN there is a CSP, there is google cloud, there is an actual retail store, there is a hardware supplier, there's a software developer, all of them as a minimum have to work together to build that ecosystem which is where we give those solutions, Right? So that's the second part. And in the third part is as they move towards cloud Native, we are really helping them change their business model to become a deVOPS. A cloud native mindset, not just a cloud native network. Alrighty, but a cloud native mindset that creates unparalleled agility and flexibility in how they work as a business. So those are the three things I would say as a response to that question >>and obviously the retail, great vertical for google to go in there, given the amazon fear out there, people want this certainly low hanging fruit. I think the devops piece is going to be a big winning opportunity to see how the developers get driven into the landscape. I think that's a huge point and well that's really great insight. A final question for you. I got you here. Um, if someone says, Hey, what's happened in the industry since 2019? We last time we had multiple Congress, they were talking speeds and feeds. Now the world has changed. We're coming out of the pandemic California's opening up. Um, there's going to be in a physical event, the world's going hybrid certainly on the event and certainly cloud what's different in the telecom industry from, you know, many, many months ago, over a year and a half ago from 2019. >>I would say primarily it's the adoption of digital everywhere, which previously, you know, there were all these inhibitions and oh would this work? Would my customer systems become fully digital? Would I be able to offer a are we are experiences? Ah, that's a futuristic thing, you know, And suddenly the pandemic has created this acceleration that says, oh, even post pandemic, half my customers are always gonna talk to me why our digital channel only, which means the way they experience us has to be through these new experiences. Whether it's a are we are, whether it's some other types of applications. So that has been accelerated, johN and the C. S. P. S have therefore really started to go to the application and to the services, which is why you're seeing less on, You know, speeds and feeds because 5Gs here, five years being deployed. Now, how do you monetize? How can we leverage the biggest, so that's the biggest changes >>down stack and then there's the top of the stack for applications and certainly there's a lot of assets in the telecom landscape, a lot of value, A lot of re factoring going on and new opportunities that are out there. Great, great conversation. Well thank you Wolf Pataca, Managing Director, telecom industry. So thanks for coming on the key. Appreciate it. >>Thank you john thank you for having me. Okay. >>Mobile Rule Congress here in person and hybrid and remote. I'm john for a host of the cube. Thank you for watching. We are here in person at the Cloud City Expo community area. Thanks for watching.

>>what? Hello, I'm john free with the cube. I want to welcome Conrad Feldman, the founder and Ceo of Kwan cast here to kick off the quan cast industry summit on the demise of third party cookies. The events called the cookie conundrum, a recipe for success. The changing advertising landscape, super relevant conversation just now. More than ever. Conrad welcome to your own program kicking this off. Thanks for holding this event. It's a pleasure. Great to chat with you today. So a big fan been following your company since the founding of it. Been analytics is always the prize of any data driven company. Media. Anything's all data driven now. Um, talk about the open internet because now more than ever it's under siege. As I, as I mentioned in my open, um, we've been seeing the democratization, a new trend of decentralization. We're starting to see um, you know, everyone's present online now, Clay Shirky wrote a book called, here comes everyone in 2005. Well everyone's here. Right? So you know, we're here, it's gonna be more open. But yet people are looking at as close right now. You're seeing the big players, um, or in the data. What's your vision of this open internet? >>Well, an open internet exists for everyone. And if you think about the evolution of the internet, when the internet was created for the first time really in history, anyone that had access to the internet could publish the content, whatever they were interested in and could find an audience. And of course that's grown to where we are today, where five billion people around the world are able to engage in all sorts of content, whether that's entertainment or education, news, movies. What's perhaps not so widely understood is that most of that content is paid for by advertising and there's a lot of systems that support advertising on the open Internet and some of those are under siege today certainly. >>And what's the big pressure point? Is it just more control the data? Is it just that these walled gardens are wanting to, you know, suck the audience in there? Is that monetization driving it? What's where's the friction? >>Well, the challenges is sort of the accumulation of power into a really small number of now giant corporations who have actually reduced a lot of the friction that marketers have in spending their money effectively. And it means that those companies are capturing a disproportionate spend of the ad budgets that fund digital content. So the problem is if more of the money goes to them, less of its going to independent content creators. It's actually getting harder for independent voices to emerge and be heard. And so that's the real challenges. That has more power consolidates into just a limited number of tech giants. The funding path for the open Internet becomes constrained and there'll be less choice for consumers without having to pay for subscriptions. >>Everyone knows the more data you have the better and certainly, but the centralized power when the trend is going the other way, the consensus is everyone wants to be decentralized more truth, more trust all this is being talked about on the heels of the google's news around, you know, getting rid of third party cookies and others have followed suit. Um, what does this mean? I mean, this cookies have been the major vehicle for tracking and getting that kind of data. What is gonna be replaced with what is this all about? And can you share with us what the future will look like? >>Sure, Well, just as advertising funds the open Internet is advertising technology that supports that advertising spend. It supports sort of the business of advertising that funds the open Internet. And within all of that technology is the need for different systems to be able to align around um the identification of for example, a consumer, Have they been to this site before? Have they seen an ad before? So there's all of these different systems that might be used for advertising for measurement, for attribution, for creating personalization. And historically they've relied upon the third party cookie as the mechanism for synchronization. Well, the third party cookie has been in decline for some time. It's already mostly gone from actually apple safari browser, but google's chrome has so much control over how people access the internet. And so it was when Google announced that chrome was going to deprecate the third party cookie, that it really sort of focus the minds of the industry in terms of finding alternative ways to tailor content and ultimately to just simply measure the effectiveness of advertising. And so there's an enormous amount of um innovation taking place right now to find alternative solutions. >>You know, some are saying that the free open internet was pretty much killed when, you know, the big comes like facebook and google started bringing all this data and kind of pulls all sucks all the auction in the room, so to speak. What's this mean with cookies now getting, getting rid of um, by google has an impact publishers because is it helpful? I mean hurtful. I mean, where's the where is that, what the publisher impact? >>Well, I don't think anyone really knows right now. So first of all, cookies weren't necessarily a very good solution to the sort of the challenge of maintaining state and understanding those sorts of the delivery of advertising and so on. It's just the one that's commonly used, I think for different publishers it may mean different things. But many publishers need to be able to demonstrate the value and the effectiveness of the advertising solutions that they deliver. So they'll be innovating in terms of how they use their first party data. They'll be continuing to use contextual solutions that have long been used to create advertising relevant, relevant. I think the big question of course is how we're going to measure it that any of this is effective at all because everyone relies upon measuring advertising effectiveness to justify capturing those budgets in the first place. >>You know, you mentioned contextual come up a lot also in the other interviews we've done with the folks in the around the internet around this topic of machine learning is a big 12 What is the impact of this with the modernization of the solution? You mentioned cookies? Okay cookies, old technology. But the mechanisms in this ecosystem around it or not, it funds the open internet. What is that modern solution that goes that next level? Is it contextual metadata? Is that shared systems? What's the it's the modernization of that. >>It's all of those and and more. There's no there's no single solution to replace the third party cookie. There'll be a combination of solutions. Part of that will be alternative identity mechanisms. So you know, you will start to see more registration wars to access content so that you have what's called a deterministic identify there will be statistical models so called probabilistic models, contextual has always been important. It will become more important and it will be combined with we use contextual combining natural language processing with machine learning models to really understand the detailed context of different pages across the internet. You'll also see the use of first party data and there are discussions about shared data services as well. I think there's gonna be a whole set of different innovations that will need to inter operate and it's going to be an evolutionary process as people get used to using these different systems to satisfy the different stages of the media fulfillment cycle from research and planning to activation to measurement. >>You know, you put up walled gardens. I want to just touch on the on on this kind of concept of walled gardens and and and and compare and contrast that with the demand for community, open internet has always fostered a community vibe. You see network effects mostly in distinct user communities or subnets of sub networks. If you will kind of walled gardens became that kind of group get together but then became more of a media solution to make the user is the product, as they say, facebook's a great example, right? People talk about facebook and from that misinformation abuse walled garden is not the best thing happening right now in the world, but yet is there any other other choice? That's how they're going to make money? But yet everyone wants trust, truth community. Are they usually exclusive? How do you see this evolving, what's your take? >>Well, I think the open internet is a, is a forum where anyone can have their voice, uh, put their voice out there and have it discovered and it's in that regard, it's a it's a force for good look. I think there are there are challenges, obviously in terms of some of the some of the optimization that takes place with inside the walled gardens, which is, is sort of optimized to drive engagement can have some unintended consequences. Um obviously that's something that's, that's broadly being discussed today and the impact on society, but sort of more at a more pointed level, it's just the absorption of advertising dollars. There's a finite amount of money from advertisers. It's estimated to be $400 billion this year in digital advertising. So it's a huge amount of money in terms of funding the open Internet, which sounds great except for its increasingly concentrated in a tiny number of companies. And so, you know, our job at Quan cast as champions of the free and open Internet is to help direct money effectively to publishers across the open internet and give advertisers a reliable, repeatable way of accessing the audiences that they care about in the environment they care about and delivering advertising results. >>It's a publisher, we care a lot about what our audience wants and try to serve them and listen to them. If we could get the data, we want that data and then also broker in the monetization with advertisers, who might want to reach that audience in whatever way. So this brings up the question of, you know, automation and role of data. You know, this is a huge thing to having that data closed loop, if you will for for publishers. But yet most publishers are small, some niche. And even as they can become super large, they don't have all the data and more, the more data, the better the machine learning. So what's the answer to this as it goes forward? How do we get there? What's the dots that that we need to connect to get that future state? >>So I think it takes it takes companies working together effectively. I think a really important part of it is, is a more direct conversation with consumers. We've seen that change beginning to happen over the past few years with the introduction of regulations that require clear communication to consumers about the data that's captured. And y and I think that creates an opportunity to explain to your audience is the way in which content is funded. So I think that consumer that consumer conversation will be part of the collective solution. >>You know, I want to as we wind down this kickoff segment, get your thoughts and vision around um, the evolution of the internet and you guys have done some great work at quan Cast is well documented, but everyone used to talk about traffic by traffic, then it became cost of acquisitions. PPC search. This is either mechanisms that people have been using for a long, long time, then you know, your connections but audience is about traffic, audience traffic. If this if my family is online, doesn't it become about networks and the people. So I want to get your thoughts and your vision because if community is going to be more important than people agree that it is and things are gonna be decentralized, more openness, more voices to be heard. You need to dress ability. The formation of networks and groups become super important. What's your vision on that? >>So my vision is to create relevance and utility for consumers. I think that's one of the things that's often forgotten is that when we make advertising more relevant and useful for consumers, it automatically fulfils the objectives that publishers and marketers have, everyone wins when advertising is more relevant. And our vision is to make advertising relevant across the entire open internet so that that ad supported model can continue to flourish and that five billion and hopefully many more billions in the future, people around the world have access to high quality, diverse content. >>If someone asked you Conrad, what is quant cast doing to make the open internet viable now that cookies are going away? What's the answer? >>So well, the cookie pieces is a central piece of it in terms of finding solutions that will enable sort of planning activation and measurement post cookies and we have a lot of innovation going on. There were also working with a range of industry bodies and our and our partners to build solutions for this. What we're really trying to do is to make buying the open internet as straightforward for marketers as it is today and buying the walled gardens. The reason the walled gardens capture so much money is they made it really easy for marketers to get results, marketers would like to be able to spend their money across all of the diverse publishes the open internet. You know, our job at Comcast is to make it just as easy to effectively spend money in funding the content that they really care about in reaching the audiences that they want. >>Great stuff. Great Mission. Conrad, thanks for coming on. Conrad Feldmann founder and Ceo here at the cookie conundrum recipe for success event, Quant Cast Industry summit on the demise of third party cookies. Thank you. Conrad appreciate it. Thank you. Yeah, I'm john ferrier, stay with us for more on the industry event around the middle cookies. Mhm Yeah, yeah, thank you. Mhm. Welcome back to the Qantas industry summit on the demise of third party cookies, the cookie conundrum, a recipe for success. I'm john furrier host of the cube, the changing landscape of advertising is here and shit Gupta, founder of you of digital is joining us chief. Thanks for coming on this segment. Really appreciate, I know you're busy, you've got two young kids as well as providing education to the digital industry, you got some kids to take care of and train them to. So welcome to the cube conversation here as part of the program. >>Yeah, thanks for having me excited to be here. >>So the office of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big 34 tech players dominate the marketplace so clearly in a major inflection point and we've seen this movie before Web mobile revolution which was basically a reply platform NG of capabilities. But now we're in an error of re factoring the industry, not re platt forming a complete changing over of the value proposition. So a lot at stake here as this open web, open internet, global internet evolves. What are your, what's your take on this, this industry proposals out there that are talking to this specific cookie issue? What does it mean? And what proposals are out there? >>Yeah, so, you know, I I really view the identity proposals and kind of to to kind of groups, two separate groups. So on one side you have what the walled gardens are doing and really that's being led by google. Right, so google um you know, introduce something called the privacy sandbox when they announced that they would be deprecating third party cookies uh as part of the privacy sandbox, they've had a number of proposals unfortunately, or you know, however you want to say they're all bird themed for some reason, I don't know why. Um but the one, the bird theme proposal that they've chosen to move forward with is called flock, which stands for Federated learning of cohorts. And essentially what it all boils down to is google is moving forward with cohort level learning and understanding of users in the future after third party cookies, unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting tracking purposes. And so that's on one side of the equation, it's what google is doing with flock and privacy sandbox now on the other side is, you know, things like unified I. D. Two point or the work that I. D five is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, unified I. D. Two point oh comes to mind because it's the one that's probably got the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it and unified, I need to point out again is user level. So it's it's basically taking data that's authenticated data from users across various websites you know that are logging in and taking those authenticated users to create some kind of identity map. And so if you think about those two work streams right, you've got the walled gardens and or you know, google with flock on one side and then you've got unified I. D. Two point oh and other I. D. Frameworks for the open internet. On the other side, you've got these two very differing type of approaches to identity in the future. Again on the google side it's cohort level, it's going to be built into chrome. Um The idea is that you can pretty much do a lot of the things that we do with advertising today, but now you're just doing it at a group level so that you're protecting privacy, whereas on the other side of the open internet you're still getting down to the user level. Um And that's pretty powerful. But the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw is under five of all website traffic is authenticated. So really if you if you simplify things you boil it all down, you have kind of these two very differing approaches. >>I guess the question it really comes down to what alternatives are out there for cookies and which ones do you think will be more successful? Because I think, you know, the consensus is at least from my reporting, in my view, is that the world agrees. Let's make it open, Which one is going to be better. >>Yeah, that's a great question, john So as I mentioned, right, we have we have to kind of work streams here, we've got the walled garden work streams, work stream being led by google and their work around flock, and then we've got the open internet, right? Let's say unified I. D to kind of represents that. I personally don't believe that there is a right answer or an endgame here. I don't think that one of them wins over the other, frankly, I think that, you know, first of all, you have those two frameworks, neither of them are perfect, they're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution. Right? So they're saying, hey, we use, you know, an open I. D. Framework in this way to get down to the user level and use that authenticated data and that's important. But we don't have all the scale. So now we go to google and we go to flock to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce, right? We have some of our own data, we have some of our own partnerships, we're gonna bring that in and layer it on top. Right? And so really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both. With a little extra something on top. I think that's that's what we're starting to see out of a lot of companies in the space. And I think that's frankly where we're headed. >>What do you think the industry will evolve to, in your opinion? Because I think this is gonna, you can't ignore the big guys on this because these programmatic you mentioned also the data is there. But what do you think the market will evolve to with this, with this conundrum? >>So, so I think john where we're headed? You know, I think we're right now we're having this existential existential crisis, right? About identity in this industry, because our world is being turned upside down, all the mechanisms that we've used for years and years are being thrown out the window and we're being told they were gonna have new mechanisms, Right? So cookies are going away device ids are going away and now we got to come up with new things and so the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Like everyone's always talking about identity right now, where do I think this is going if I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today. Right? Forget about all the changes. Just think about it now and maybe a few years before today, Identity for marketers in my opinion has been a little bit of a checkbox activity. Right? It's been hey, um, okay, uh, you know ad tech company or a media company, do you have an identity solution? Okay. Tell me a little bit more about it. Okay, Sounds good. That sounds good. Now can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business? And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know. Yes, You have it. Okay, great. Let's move on, type of thing. Right. And so that, that's, that's kind of where we've been now, all of a sudden The cookies are going away, the device ids are going away. And so the world is turning upside down in this crisis of how are we going to keep doing what we were doing for the last 10 years in the future. So everyone's talking about it and we're trying to re engineer right? The mechanisms now if I was to look into the crystal ball right 2 3 years from now where I think we're headed is not much is going to change. And what I mean by that john is um uh I think that marketers will still go to companies and say do you have an ID solution? Okay tell me more about it. Okay uh Let me understand a little bit better. Okay you do it this way. Sounds good. Now the ways in which companies are going to do it will be different right now. It's flock and unified I. D. And this and that right. The ways the mechanisms will be a little bit different but the end state right? Like the actual way in which we operate as an industry and kind of like the view of the landscape in my opinion will be very simple or very similar, right? Because marketers will still view it as a tell me you have an ID solution. Make me feel good about it. Help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment where we do have to talk about and figure out what we're going to do in the future. My just my viewpoint is that the future will actually not look all that different than the present. >>And I'll say the user base is the audience. Their their data behind it helps create new experiences, machine learning and Ai are going to create those and we have the data you have the sharing it or using it as we're finding shit Gupta great insight dropping some nice gems here. Founder of you of Digital and also the Adjunct professor of Programmatic advertising at Levi School of Business and santa Clara University professor. Thank you for coming dropping the gems here and insight. Thank you. >>Thanks a lot for having me john really appreciate >>it. Thanks for watching. The cooking 100 is the cube host Jon ferrier me. Thanks for watching. Mhm. Yeah. Mhm. Hello welcome back to the cookie conundrum recipe for success and industry conference and summit from Guanacaste on the demise of third party cookies. Got a great industry panel here to break it down chris Gunther Senior Vice president Global Head of programmatic at news corp chris thanks for coming on Zal in Managing Director Solutions at Z axis and Summer Simpson. Vice president Product at quan cast stellar panel. Looking forward to this conversation. Uh thanks for coming on and chatting about the cookie conundrum. Thank you for having us. So chris we'll start with you at news corp obviously a major publisher deprecation of third party cookies affects everyone. You guys have a ton of traffic, ton of audience across multiple formats. Um, tell us about the impact to you guys and the reliance he has had on them. And what are you gonna do to prepare for this next level change? >>Sure. I mean, I think like everyone in this industry there's uh a significant reliance and I think it's something that a lot of talk about audience targeting but obviously that reliance on third party cookies pervasive across the whole at tech ecosystem Martek stack. And so you know, we have to think about how that impact vendor vendors, we work with what it means in terms of use cases across marketing, across advertising, across site experience. So, you know, without a doubt, it it's it's significant, but you know, we look at it as listen, it's disruptive, uh, disruption and change is always a little scary. Um, but overall it's a, it's a long overdue reset. I mean, I think that, you know, our perspective is that the cookies, as we all know was it was a crutch, right sort of a technology being used in way it shouldn't. Um, and so as we look at what's going to happen presumably after Jan 2022 then it's, it's a good way to kind of fix on some bad practices practices that lead to data leakage, um, practice or devalue for our perspective, some of the, you know, we offered as as publishers and I think that this is a key thing is that we're not just looking to as we look at the post gender world, not just kind of recreating the prior world because the prior world was flawed or I guess you could say the current world since it hasn't changed yet. But the current world is flawed. Let's not just not, you know, let's not just replicate that. Let's make sure that, you know, third party cookie goes away. Other work around like fingerprinting and things like that. You know, also go away so philosophically, that's where our heads at. And so as we look at how we are preparing, you know, you look at what are the core building blocks of preparing for this world. Obviously one of the key ones is privacy compliance. Like how do we treat our users with consent? Yeah, obviously. Are we um aligned with the regulatory environments? Yeah. In some ways we're not looking just a Jan 2022, but Jan 23 where there's gonna be the majority of our audiences we covered by regulation. And so I think from regulation up to data gathering to data activation, all built around an internal identifier that we've developed that allows us to have a consistent look at our users whether they're logged in or obviously anonymous. So it's really looking across all those components across all our sites and in all in a privacy compliant way. So a lot of work to be done, a lot of work in progress. But we're >>excited about what's going on. I like how you framed at Old world or next gen kind of the current situation kind of flawed. And as you think about programmatic, the concept is mind blowing and what needs to be done. So we'll come back to that because I think that original content view is certainly relevant, a huge investment and you've got great content and audience consuming it from a major media standpoint. Get your perspective on the impact because you've got clients who want to get their their message out in front of the audience at the right time, at the right place and the right context. Right, So your privacy, you got consent, all these things kind of boiling up. How do you help clients prepare? Because now they can go direct to the consumer. Everyone, everyone has a megaphone, now, everyone's, everyone's here, everyone's connected. So how are you impacted by this new notion? >>You know, if if the cookie list future was a tic tac, dance will be dancing right now, and at least into the next year, um this has been top of mind for us and our clients for quite some time, but I think as each day passes, the picture becomes clearer and more in focus. Uh the end of the third party cookie does not mean the end of programmatic. Um so clients work with us in transforming their investments into real business outcomes based on our expertise and based on our tech. So we continue to be in a great position to lead to educate, to partner and to grow with them. Um, along this uh cookie list future, the impact will be all encompassing in changing the ways we do things now and also accelerating the things that we've already been building on. So we take it from the top planning will have a huge impact because it's gonna start becoming more strategic around real business outcomes. Uh where Omni channel, So clients want to drive outcomes, drew multiple touch points of a consumer's journey, whether it has programmatic, whether it has uh cookie free environment, like connected tv, digital home audio, gaming and so forth. So we're going to see more of these strategic holistic plans. Creative will have a lot of impact. It will start becoming more important with creative testing. Creative insights. You know, creative in itself is cookie list. So there will be more focused on how to drive uh brand dialogue to connect to consumers with less targeting. With less cookies, with the cohesiveness of holistic planning. Creative can align through multiple channels and lastly, the role of a. I will become increasingly important. You know, we've always looked to build our tech our products to complement new and existing technology as well as the client's own data and text back to deliver these outcomes for them. And ai in its core it's just taking input data uh and having an output of your desired outcome. So input data could be dSP data beyond cookies such as browser such as location, such as contextual or publisher taking clients first party data, first party crm data like store visitation, sales, site activity. Um and using that to optimize in real time regardless of what vendor or what channel we're on. Um So as we're learning more about this cookie list dance, we're helping our clients on the steps of it and also introducing our own moves. >>That's awesome. Data is going to be a key value proposition, connecting in with content real time. Great stuff. Somewhere with your background in journalism and you're the tech VP of product at quan cast. You have the keys to the kingdom over there. It's interesting Journalism is about truth and good content original content. But now you have a data challenge problem opportunity on both sides, brands and publishers coming together. It's a data problem in a way it's a it's a tech stack, not so much just getting the right as to show up at the right place the right time. It's really bigger than that now. What's your take on this? >>Um you know, >>so first >>I think that consumers already sort of like except that there is a reasonable value exchange for their data in order to access free content. Right? And that's that's a critical piece for us to all kind of like understand over the past. Hi guys, probably two years since even even before the G. D. P. R. We've been doing a ton of discovery with customers, both publishers and marketers. Um and so you know, we've kind of known this, this cookie going away thing has been coming. Um And you know, Google's announcement just kind of confirmed it and it's been, it's been really, really interesting since Google's announcement, how the conversations have changed with with our customers and other folks that we talked to. And I've almost gone from being like a product manager to a therapist because there's such an emotional response. Um you know, from the marketing perspective, there's real fear there. There's like, oh my God, how you know, it's not just about, you know, delivering ads, it's about how do I control frequency? How do I, how do I measure, you know, success? Because the technology has has grown so much over the years to really give marketers the ability to deliver personalized advertising, good content, right. The consumers um and be able to monitor it and control it so that it's not too too intrusive on the publisher perspective side, we see slightly different response. It's more of a yes, right. You know, we're taking back control and we're going to stop the data leakage, we're going to get the value back for our inventory. Um and that both things are a good thing, but if it's, if it's not managed, it's going to be like ships passing in the night, right? In terms of um of, you know, they're there, them coming together, right, and that's the critical pieces that they have to come together. They have to get closer, you got to cut out a lot of that loom escape in the middle so that they can talk to each other and understand what's the value exchange happening between marketers and publishers and how do we do that without cookies? >>It's a fascinating, I love love your insight there. I think it's so relevant and it's got broader implications because, you know, if you look at how data's impact, some of these big structural changes and re factoring of industries, look at cyber security, you know, no one wants to share their data, but now if they share they get more insight, more machine learning, benefit more ai benefit. So now we have the sharing notion, but that goes against counter the big guys that want to wall garden, they want to hoard all the data and and control that to provide their own personalization. So you have this confluence of, hey, I want to hoard the data and then now I want to share the data. So so christmas summer you're in the, in the wheelhouse, you got original content and there's other providers out there. So is there the sharing model coming with privacy and these kinds of services? Is the open, come back again? How do you guys see this uh confluence of open versus walled gardens, because you need the data to make machine learning good. >>So I'll start uh start off, I mean, listen, I think you have to give credit to the walled gardens have created, I think as we look as publishers, what are we offering to our clients, what are we offering to the buy side? We need to be compelling. We shouldn't just be uh yeah, actually as journalists, I think that there is a case of the importance of funding journalism. Um but ultimately we need to make sure we're meeting the KPI is and the business needs of the buy side. And I think around that it is the sort of three core pillars that its ease of access, its scope of of activation and targeting and finally measurable results. So as I think is us as an individual publishers, so we have, we have multiple publications. So we do have scale. But then in partnership with other publishers perhaps to organizations like pre bid, you know, I think we can, you know, we're trying to address that and I think we can offer something that's compelling um, and transparent in terms of what these results are. But obviously, you know, I want to make sure it's clear transparent terms of results, but obviously where there's privacy in terms of the data and I think the form, you know, I think we've all heard a lot like data clean rooms, a lot of them out there flogging those wears. I think there's something valuable but you know, I think it's the right who is sort of the right partner or partners um and ultimately who allows us to get as close as possible to the buy side. And so that we can share that data for targeting, share it for perhaps for measurement, but obviously all in a privacy compliant >>way summer, what's your take on this? Because you talk about the future of the open internet democratization, the network effect that we're seeing in Vire al Itty and across multiple on the on the channels. Is that pointed out what's happening? That's the distribution now. So um that's almost an open garden model. So it's like um yeah, >>yeah, it's it's um you know, back in the day, you know, um knight ridder who was who was the first group that I that I worked for, um you know, each of those individual properties, um we're not hugely valuable on their own from a digital perspective, but together as a unit, they became valuable, right, and got scale for advertisers. Now we're in a place where, you know, I kind of think that each of those big networks are going to have to come together and work together to compare in size to the, to the world gardens. Um, and yeah, this is something that we've talked about before and an open garden. Um, I think that's the, that's the definitely the right route to take. And I and I agree with chris it's, it's about publishers getting as close to the market. Is it possible working with the tech companies that enable them to do that and doing so in a very privacy centric >>way. So how do we bring the brands and agencies together to get ready for third party cookies? Because there is a therapist moment here of it's gonna be okay. The parachute will open. The future is not gonna be as as grim. Um, it's a real opportunity. But if managed properly, what's your take on this is just more first party data strategy and what's your assessment of this? >>So we collaborated right now with ball grants on how did this still very complex cookie list future. Um, you know what's going to happen in the future? 2, 6 steps that we can take right now and market should take. Um, The first step is to gather intel on what's working on your current campaign, analyzing the data sets across cookie free environment. So you can translate those tactics eventually when the cookies do go away. So we have to look at things like temperature or time analysis. We could look at log level data. We could look at site analytics data. We can look at brand measurement tools and how creative really impacts the campaign success. The second thing we can look at is geo targeting strategies. The geo target strategy has been uh underrated because the granularity and geo data could go down all the way to the local level, even beyond zip code. So for example the census black data and this is especially important for CPG brands. So we're working closely with the client teams to understand not only the online data but the offline data and how we can utilize that in the future. Uh We want to optimize investments around uh markets that are working so strong markets and then test and underperforming markets. The third thing we can look at is contextual. So contextual by itself is cookie free. Uh We could build on small scale usage to test and learn various keywords and content categories based sets. Working closely with partners to find ways to leverage their data to mimic audiences that you are trying to target right now with cookies. Um the 4th 1 is publisher data or publisher targeting. So working with your publishers that you have strong relationships with who can curate similar audiences using their own first party data and conducting RFs to understand the scale and reach against your audience and their future role maps. So work with your top publishers based on historical data to try to recreate your best strategies. The 15 and I think this is very important is first party data, you know, that's going to matter more than ever. In the calculus future brands will need to think about how to access and developed the first party data starting with the consumers seeing a value in exchange for the information. It's a gold mine and understanding of consumer, their intent, the journey um and you need a really great data science team to extract insights out of that data, which will be crucial. So partner with strategic onboarding vendors and vet their ability to accept first party data into a cleaner environment for targeting for modeling for insight. And lastly, the six thing that we can do is begin to inform prospect prospecting by dedicating test budget to start gaining learnings about cookie list 11 place that we can start and it is under invested right now is Safari and Firefox. They have been calculus for quite some time so you can start here and begin testing here. Uh work with your data scientist team to understand the right mix is to to target and start exploring other channels outside of um just programmatic cookies like CTV digital, out of home radio gaming and so forth. So those are the six steps that we're taking right now with our clients to uh prepare and plan for the cookie list future. >>So chris let's go back to you. What's the solution here? Is there one, is there multiple solutions? What's the future look like for a cookie was future? >>Uh I think the one certain answers, they're definitely not just one solution. Um as we all know right now there there seems to be endless solutions, a lot of ideas out there, proposals with the W three C uh work happening within other industry bodies uh you know private companies solutions being offered and you know, it's a little bit of it's enough to make everyone's head spin and to try to track it to understand and understand the impact. And as a publisher were obviously a lot of people are knocking on our door. Uh they're saying, hey our solution is one that is going to bring in lots of money, you know, the all the buy side is going to use it. This is the one like I ma call to spend um, and so expect here and so far is that none of these solutions are I think everyone is still testing and learning no one on the buy side from our, from our knowledge is really committed to one or a few. It's all about a testing stage. I think that, you know, putting aside all that noise, I think what matters the most to us as publisher is actually something summer mentioned before. It's about control. You know, if we're going to work with a again, outside of our sort of, you know, internal identifier work that we're doing is we're going to work with an outside party or outside approach doesn't give us control as a publisher to ensure that it is, we control the data from our users. There isn't that data leakage, it's probably compliant. What information gets shared out there. What is it, what's released within within the bid stream? Uh If it is something that's attached to a somewhat declared user registered user that if that then is not somehow amplified or leverage off on another site in a way that is leveraging bit stream data or fingerprinting and going against. I think that the spirit of what we're trying to do in a post third party cookie world so that those controls are critical and I think they have those controls, his publisher, we have collectively be disciplined in what solutions that we we test out and what we eventually adopt. But even when the adoption point arrives, uh definitely it will not be one. There will be multiple because it's just too many use cases to address >>great, great insight there from, from you guys, news corp summer. Let's get back to you. I want to get your thoughts. You've been in many waves of innovation ups and downs were on a new one. Now we talked about the open internet democratization. Journalism is under a lot of pressure now, but there's now a wave of quality people really leaning in towards fighting misinformation, understanding truth and community and date is at the heart of it. What do you see as the new future for journalists, reward journalism is our ways their path forward. >>So there's uh, there's what I hope is going to happen. Um, and then I'm just gonna ignore what could write. Um, you know, there's there's a trend in market right now, a number of fronts, right? So there are marketers who are leaning into wanting to spend their marketing dollars with quality journalists, focusing on bipac owned and operated, really leaning into into supporting those businesses that have been uh, those publishers that have been ignored for years. I really hope that this trend continues. Um We are leaning into into helping um, marketers curate that supply right? And really, uh, you know, speak with their dollars about the things that that they support. Um, and uh, and and value right in market. So I'm hoping that that trend continues and it's not just sort of like a marketing blip. Um, but we will do everything possible to kind of like encourage that behavior and and give people the information they need to find, you know, truly high quality journalism. >>That's awesome chris Summer. Thanks for coming on and sharing your insight on this panel on the cookie list future. Before we go, just quick summary each of you. If you don't mind just giving a quick sound bite or bumper sticker of what we can expect. If you had to throw a prediction For what's going to happen in the next 24 months Chris We'll start with you. >>Uh it's gonna be quite a ride. I think that's an understatement. Um I think that there, I wouldn't be surprised if if google delays the change to the chrome by a couple of months and and may give the industry some much needed time, but no one knows. I guess. I guess I'm not except for someone somewhere deep within chrome. So I think we all have to operate in a way that changes to happen, changes to happen quickly and it's gonna cover across all facets of the industry, all facets of from advertising, marketing. So just be >>prepared. >>Yeah, along the same lines, be prepared, nobody knows what's going to happen in the future. Uh You know, while dancing in this together. Uh I think um for us it's um planning and preparing and also building on what we've already been working on. Um So omni channel ai um creative and I think clients will uh lean more into those different channels, >>awesome. So we'll pick us home, last word. >>I think we're in the throwing spaghetti against the wall stage. Right, so this is a time of discovery of leaning in trying everything out, Learning and iterating as fast as we possibly >>can. Awesome. And I love the cat in the background over your shoulder. Can't stop staring at your wonderful cat. Thanks for coming on chris, Thanks for coming on. This awesome panel industry breakdown of the cookie conundrum. The recipe for success data ai open. Uh The future is here, it's coming, it's coming fast. I'm john fryer with the cube. Thanks for watching. Mhm. Yeah. Mhm. Mhm. Welcome back to the Quant Cast industry summit on the demise of third party cookies. The cookie conundrum, a recipe for success. We're here peter day. The cto of quad cast and crew T cop car, head of product marketing quad cast. Thanks for coming on talking about the changing advertising landscape. >>Thanks for having us. Thank you for having >>us. So we've been hearing this story out to the big players. Want to keep the data, make that centralized control, all the leverage and then you've got the other end. You got the open internet that still wants to be free and valuable for everyone. Uh what's what are you guys doing to solve this problem? Because cookies go away? What's going to happen there? How do people track things you guys are in this business first question? What is quan cast strategies to adapt to third party cookies going away? What's gonna be, what's gonna be the answer? >>Yeah. So uh very rightly said, john the mission, the Qantas mission is the champion of free and open internet. Uh And with that in mind, our approach to this world without third party cookies is really grounded in three fundamental things. Uh First as industry standards, we think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind, we've been participating >>with I. A. B. >>Tech lab, we've been part of their project Triarc. Uh same thing with pre bid, who's kind of trying to figure out the pipes of identity. Di di di di di pipes of uh of the future. Um And then also is W three C, which is the World Wide Web Consortium. Um And our engineers and our engineering team are participating in their weekly meetings trying to figure out what's happening with the browsers and keeping up with the progress they're on things such as google's block. Um The second uh sort of thing is interoperability, as you've mentioned, there are lots of different uh I. D. Solutions that are emerging. You have you I. D. Two point oh, you have live RAM, you have google's flock. Uh And there will be more, there are more and they will continue to be more. Uh We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. Uh The reason really is to meet our customers where they are at today. Our customers use multiple different data management platforms, the mps. Um and that's why we support multiple of those. Um This is not going to be much different than that. We have to meet our customers where we are, where they are at. And then finally, of course, which is at the very heart of who contrast is innovation. Uh As you can imagine being able to take all of these multiple signals in including the I. D. S. And the cohorts, but also others like contextual first party um consent is becoming more and more important. Um And then there are many other signals, like time, language geo location. So all of these signals can help us understand user behavior intent and interests um in absence of 3rd party cookies. However, uh there's there's something to note about this. They're very raw, their complex, they're messy all of these different signals. Um They are changing all the time, they're real time. Um And there's incomplete information isolation. Just one of these signals cannot help you build a true and complete picture. So what you really need is a technology like AI and machine learning to really bring all of these signals together, combine them statistically and get an understanding of user behavior intent and interests and then act on it, be it in terms of providing audience insights um or responding to bid requests and and so on and so forth. So those are sort of the three um fundamentals that our approach is grounded in which is industry standards, interoperability and and innovation. Uh and you know, you have peter here, who is who is the expert So you can dive much deeper into >>it. Is T. T. O. You've got to tell us how is this going to actually work? What are you guys doing from a technology standpoint to help with data driven advertising in a third party cookie list world? >>Well, we've been um This is not a shock, you know, I think anyone who's been close to his space has known that the 3rd Party Cookie has been um uh reducing inequality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really google chrome making a, making the changes that they're gonna be making. So we've been investing in the space for many years. Um and we've had to make a number of hugely diverse investment. So one of them is in how as a marketer, how do I tell if my marketing still working in the world without >>computers? The >>majority of marketers completely reliant on third party cookies today to tell them if they're if they're marketing is working or not. And so we've had to invest heavily and statistical techniques which are closer to kind of economic trick models that markets are used to things like out of home advertising, It's going to establishing whether they're advertising is working or not in a digital environment actually, >>just as >>often, you know, as is often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement has often mistaken precision for accuracy. And there's a real opportunity to kind of see the wood for the trees if you like. And start to come with better methods of measuring the affections of advertising without third party cookies. And in fact to make countless other investments in areas like contextual modeling and and targeting that third party cookies and and uh, connecting directly to publishers rather than going through this kind of bloom escape that's gonna tied together third party cookies. So if I was to enumerate all the investments we've made, I think we'll be here till midnight but we have to make a number of vestments over a number of years and that level investments only increasing at the moment. >>Peter on that contextual. Can you just double click on that and tell us more? >>Yeah, I mean contextual is unfortunately these things, this is really poorly defined. It can mean everything from a publisher saying, hey, trust us, this dissipated about CVS to what's possible now and has only really been possible the last couple of years, which is to build >>statistical >>models of the entire internet based on the content that people are actually consumed. And this type of technology requires massive data processing capabilities. It's able to take advantage of the latest innovations in there is like natural language processing and really gives um computers are kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize, organized the Internet in terms of the types of content of pages. So this type of technology has only been possible the last two years and we've been using contextual signals since our inception, it's always been massively predictive in terms of audience behaviours, in terms of where advertising is likely to work. And so we've been very fortunate to keep the investment going um and take advantage of many of these innovations that have happened in academia and in kind of uh in adjacent areas >>on the ai machine learning aspect, that seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and ai factoring into your platform? >>I think it's, it's how we've always operated right from our interception when we started as a measurement company, the way that we were giving our customers at the time, we were just publishers, just the publisher side of our business insights into who their audience was, were, was using machine learning techniques. And that's never really changed. The foundation of our platform has always been, has always been machine learning from from before. It was cool. A lot of our kind of, a lot of our core teams have backgrounds in machine learning phds in statistics and machine learning and and that really drives our our decision making. I mean, data is only useful if you can make sense of it and if you can organize it and if you can take action on it and to do that at this kind of scout scale, it's absolutely necessary to use machine learning technology. >>So you mentioned contextual also, you know, in advertising, everyone knows in that world that you've got the contextual behavioural dynamics, the behavior that's kind of generally everyone's believing is happening. The consensus is undeniable is that people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't wanna get walled into a walled garden, nobody wants to be in the world, are they want to be free to pop around and visit sites is more horizontal scalability than ever before. Yet, the bigger players are becoming walled garden, vertical platforms. So with future of ai the experience is going to come from this data. So the behavior is out there. How do you get that contextual relevance and provide the horizontal scale that users expect? >>Yeah, I think it's I think it's a really good point and we're definitely this kind of tipping point. We think, in the broader industry, I think, you know, every published right, we're really blessed to work with the biggest publishers in the world, all the way through to my mom's vlog, right? So we get to hear the perspectives of publishers at every scale. I think they consistently tell us the same thing, which is they want to more directly connected consumers, they don't wanna be tied into these walled gardens, which dictate how they must present their content and in some cases what content they're allowed to >>present. >>Um and so our job as a company is to really provide level >>the playing field a little bit, >>provide them the same capabilities they're only used to in the walled gardens, but let's give them more choice in terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively by making their audiences in their environments discoverable by marketers measurable by marketers and connect them as directly as possible to make that kind of ad funded economic model as effective in the open Internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet as it is in social media. It should be as effective for them to reach people in the environment is really high quality content as it is on facebook. And so we invest a lot of a lot of our R and D dollars in making that true. We're now live with the Comcast platform, which does exactly that. And as third party cookies go away, it only um only kind of exaggerated or kind of further emphasizes the need for direct connections between brands and publishers. And so we just wanna build the technology that helps make that true and gives the kind of technology to these marketers and publishers to connect and to deliver great experiences without relying on these kind of walled >>gardens. Yeah, the Director Director, Consumer Director audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for for that's happening in this new world? How do you ingest the content and just this consent uh signaling? >>Uh we were really fortunate to have an amazing, amazing R and D. Team and, you know, we've had to do all sorts to make this, you need to realize our vision. This has meant things like, you know, we have crawlers which scan the entire internet at this point, extract the content of the pages and kind of make sense of it and organize it uh, and organize it for publishers so they can understand how their audiences overlap with potential competitors or collaborators. But more importantly, organize it for marketers. So you can understand what kind of high impact opportunities are there for them there. So, you know, we've had to we've had to build a lot of technology. We've had to build analytics engines, which can get answers back in seconds so that marketers and publishers can kind of interact with their own data and make sense of it and present it in a way that's compelling and help them drive their strategy as well as their execution. We've had to invest in areas like consent management because we believe that a free and open internet is absolutely reliant on trust and therefore we spend a lot of our time thinking about how do we make it easy for end users to understand who has access to their data and easy for end users to be able to opt out. And uh and as a result of that, we've now got the world's most widely adopted adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. Were fortunate enough to have had a large enough R and D budget over the last four or five years, make a number investments, everything from consent and identity through context, your signals through the measurement technologies, which really bring advertisers >>and Publishers places together great insight. Last word for you is what's the what's the customer view here as you bring these new capabilities of the platform, uh what's what are you guys seeing as the highlight uh from a platform perspective? >>So the initial response that we've seen from our customers has been very encouraging, both on the publisher side as well as the marketer side. Um I think, you know, one of the things we hear quite a lot is uh you guys are at least putting forth a solution, an actual solution for us to test Peter mentioned measurement, that really is where we started because you cannot optimize what you cannot measure. Um so that that is where his team has started and we have some measurement very, very uh initial capabilities still in alpha, but they are available in the platform for marketers to test out today. Um so the initial response has been very encouraging. People want to engage with us um of course our, you know, our fundamental value proposition, which is that the Qantas platform was never built to be reliant on on third party data. These stale segments like we operate, we've always operated on real time live data. Um The second thing is, is our premium publisher relationships. We have had the privilege of working like Peter said with some of the um biggest publishers, but we also have a very wide footprint. We have first party tags across um over 100 million plus web and mobile destinations. Um and you know, as you must have heard like that sort of first party footprint is going to come in really handy in a world without third party cookies, we are encouraging all of our customers, publishers and marketers to grow their first party data. Um and so that that's something that's a strong point that customers love about us and and lean into it quite a bit. Um So yeah, the initial response has been great. Of course it doesn't hurt that we've made all these are in the investments. We can talk about consent. Um, and you know, I often say that consent, it sounds simple, but it isn't, there's a lot of technology involved, but there's lots of uh legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, very good response. Initially >>democratization. Everyone's a publisher. Everyone's a media company. They have to think about being a platform. You guys provide that. So I congratulate Peter. Thanks for dropping the gems there. Shruti, thanks for sharing the product highlights. Thanks for, for your time. Thank you. Okay, this is the quan cast industry summit on the demise of third party cookies. And what's next? The cookie conundrum. The recipe for success with Kwan Cast. I'm john free with the cube. Thanks for watching. Mm

>>mhm Yes. Welcome back to the Qantas industry summit on the demise of third party cookies, the cookie conundrum, a recipe for success. I'm john furrier host of the cube. The changing landscape of advertising is here and Chip Gupta, founder of you of digital is joining us Chip, thanks for coming on this segment. Really appreciate, I know you're busy, you've got two young kids as well as providing education to the digital industry. You got some kids to take care of and train them to. So welcome to the cube conversation here as part of the program. >>Yeah, thanks for having me excited to be here. >>So the house of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big 34 tech players dominate the marketplace. So clearly in a major inflection point and we've seen this movie before Web mobile revolution, which was basically a reply platform NG of capabilities. But now we're in an error of re factoring the industry, not re platt forming a complete changing over of the value proposition. So a lot at stake here as this open web, open internet global internet evolved. What are your, what's your take on this, this industry proposals out there that are talking to this specific cookie issue? What does it mean? And what proposals are out there? >>Yeah, so, you know, I I really view the identity proposals and kind of to to kind of groups, two separate groups. So on one side you have what the walled gardens are doing and really that's being led by google. Right, so google um you know, introduce something called the privacy sandbox when they announced that they would be deprecating third party cookies uh as part of the privacy sandbox, they've had a number of proposals unfortunately, or you know, however you want to say they're all bird themed for some reason, I don't know why. Um but the one the bird theme proposal that they've chosen to move forward with is called flock, which stands for Federated learning of cohorts. And essentially what it all boils down to is google is moving forward with cohort level Learning and understanding of users in the future after 3rd party cookies, unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting tracking purposes. And so that's on one side of the equation, it's what google is doing with flock and privacy sandbox. Now On the other side is, you know, things like unified, I need to point or the work that 85 is doing around building new identity frameworks for the entire space, that actually can still get down to the user level. Right? And so again, unified I. d 2.0 comes to mind because it's the one that's probably got the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it and unified, I need to point out again is user level. So it's it's basically taking data that's authenticated data from users across various websites you know that are logging in and taking those authenticated users to create some kind of identity map. And so if you think about those two work streams right, you've got the walled gardens and or you know, google with flock on one side and then you've got unified I. D. Two point oh and other I. D. Frameworks for the open internet on the other side, you've got these two very differing type of approaches to identity in the future. Again on the google side it's cohort level, it's gonna be built into chrome. Um The idea is that you can pretty much do a lot of the things that we do with advertising today, but now you're just doing it at a group level so that you're protecting privacy whereas on the other side of the open internet you're still getting down to the user level. Um And that's pretty powerful. But the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw is under five of all website traffic is authenticated. So really if you if you simplify things, you boil it all down, you have kind of these two very differing approaches. >>I guess the question it really comes down to what alternatives are out there for cookies, and which ones do you think will be more successful? Because I think, you know, the consensus is at least from my reporting in my view, is that the world agrees, Let's make it open, Which one is going to be better. >>Yeah, that's a great question, john So as I mentioned, right, we have we have to kind of work streams here, we've got the walled garden work work stream being led by google and their work around flock, and then we've got the open internet, right? Let's say unified I. D to kind of represents that. I personally don't believe that there is a right answer or an endgame here. I don't think that one of them wins over the other, frankly, I think that, you know, first of all, you have those two frameworks, neither of them are perfect, they're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution. Right? So they're saying, hey, we use, you know, an open I. D. Framework in this way to get down to the user level and use that authenticated data and that's important. But we don't have all the scale. So now we go to google and we go to flock to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce, right? We have some of our own data, we have some of our own partnerships, we're gonna bring that in and layer it on top. Right? And so really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both. With a little extra something on top. I think that's, that's what we're starting to see out of a lot of companies in the space and I think that's frankly where we're headed. >>What do you think the industry will evolve to, in your opinion? Because I think this is gonna, you can't ignore the big guys on this, has these programmatic, you mentioned also the data is there. But what do you think the market will evolve to with this, with this conundrum? >>So, so I think john where we're headed? Um, you know, I think we're right now we're having this existential existential crisis, right? About identity in this industry, because our world is being turned upside down, all the mechanisms that we've used for years and years are being thrown out the window and we're being told that we're gonna have new mechanisms, right? So cookies are going away device IEDs are going away and now we got to come up with new things and so the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Like everyone's always talking about identity right now, where do I think this is going if I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today, Right? Forget about all the changes. Just think about it now and maybe a few years before today, Identity for marketers in my opinion, has been a little bit of a checkbox activity. Right? It's been, hey, um, okay, uh, you know, ad tech company or media company, do you have an identity solution? Okay. Tell me a little bit more about it. Okay. Sounds good. That sounds good. Now can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business? And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know, Yes, you have it. Okay, great. Let's move on, type of thing. Right. And so that, that's, that's kind of where we've been now, all of a sudden the cookies are going away, the device IDs are going away. And so the world is turning upside down. We're in this crisis of how are we going to keep doing what we were doing for the last 10 years in the future. So everyone's talking about it and we're trying to re engineer right? The mechanisms now if I was to look into the crystal ball right two or three years from now where I think we're headed is not much is going to change. And what I mean by that john is um I think that marketers will still go to companies and say do you have an ID solution? Okay tell me more about it. Okay uh let me understand a little bit better. Okay you do it this way. Sounds good. Now the ways in which companies are going to do it will be different right now. It's flock and unified I. D. And this and that right. The ways the mechanisms will be a little bit different but the end state right? Like the actual way in which we operate as an industry and kind of like the view of the landscape, in my opinion will be very simple or very similar, right? Because marketers will still view it as a tell me you have an ID solution, Make me feel good about it. Help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment where we do have to talk about and figure out what we're gonna do in the future. My just my viewpoint is that the future will actually not look all that different than the present. >>And I'll say the user base is the audience. Their their data behind it helps create new experiences, machine learning and Ai are going to create those and we have the data. You have the sharing it or using it as we're finding shit. Gupta great insight dropping some nice gems here, Founder of You of Digital and also the Adjunct professor of Programmatic advertising at Levi School of Business and santa Clara University Professor. Thank you for coming, dropping the gems here and insight. Thank you. >>Thanks a lot for having me john really appreciate it. >>Thanks for watching the cooking 100 is the cube host Jon ferrier. Me. Thanks for watching. Yeah. Yeah.

(upbeat electronic music) >> Welcome back to the Quantcast Industry Summit on the demise of third-party cookies. The Cookie Conundrum, A Recipe for Success. I'm John Furrier, host of theCUBE. The changing landscape of advertising is here, and Shiv Gupta, founder of U of Digital is joining us. Shiv, thanks for coming on this segment. I really appreciate it. I know you're busy. You've got two young kids, as well as providing education to the digital industry. You got some kids to take care of and train them too. So, welcome to the cube conversation here as part of the program. >> Yeah, thanks for having me. Excited to be here. >> So, the house of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big three, four tech players dominate the marketplace. So, clearly in a major inflection point. And you know, we've seen this movie before. Web, now mobile revolution. Which was basically a re-platforming of capabilities, but now we're in an era of refactoring the industry, not replatforming. A complete changing over of the value proposition. So, a lot at stake here as this open web, open internet-- global internet, evolves. What are your, what's your take on this? There's industry proposals out there that are talking to this specific cookie issue? What does it mean and what proposals are out there? >> Yeah, so, you know, I really view the identity proposals in kind of two kinds of groups. Two separate groups. So, on one side you have what the walled gardens are doing. And really that's being led by Google, right? So, Google introduced something called the Privacy Sandbox when they announced that they would be deprecating third-party cookies. And as part of the Privacy Sandbox, they've had a number of proposals. Unfortunately, or you know, however you want to say, they're all bird-themed, for some reason I don't know why. But the one, the bird-themed proposal that they've chosen to move forward with is called FLOC, which stands for Federated Learning of Cohorts. And, essentially what it all boils down to is Google is moving forward with cohort level learning and understanding of users in the future after third-party cookies. Unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting and tracking purposes. And so, that's on one side of the equation. It's what Google is doing with FLOC and Privacy Sandbox. Now, on the other side is, you know, things like unified ID 2.0 or the work that ID5 is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, Unified ID 2.0 comes to mind because it's the one that's probably gotten the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it. And Unified ID 2.0 again is user level. So, it's basically taking data that's authenticated data from users across various websites that are logging in and taking those authenticated users to create some kind of identity map. And so, if you think about those two work streams, right? You've got the walled gardens and or, you know, Google with FLOC on one side. And then you've got Unified ID 2.0 and other ID frameworks for the open internet on the other side. You've got these two very different type of approaches to identity in the future. Again, on the Google side it's cohort level, it's going to be built into Chrome. The idea is that you can pretty much do a lot of the things that we do with advertising today but now you're just doing them at a group level so that you're protecting privacy. Whereas, on the other side with the open internet you're still getting down to the user level and that's pretty powerful but the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw was under 5% of all website traffic is authenticated. So, really if you simplify things and you boil it all down you have kind of these two very differing approaches. >> So we have a publishing business. We'd love to have people authenticate and get that closed loop journalism thing going on. But, if businesses wannna get this level too, they can have concerns. So, I guess my question is, what's the trade-off? Because you have power in Google and the huge data set that they command. They command a lot of leverage with that. And again, centralized. And you've got open. But it seems to me that the world is moving more towards decentralization, not centralization. Do you agree with that? And does that have any impact to this? Because, you want to harness the data, so it rewards people with the most data. In this case, the powerful. But the world's going decentralized, where there needs to be a new way for data to be accessed and leveraged by anyone. >> Yeah. John, it's a great point. And I think we're at kind of a crossroads, right? To answer that question. You know, I think what we're hearing a lot right now in the space from publishers, like yourself, is that there's an interesting opportunity right now for them, right? To actually have some more control and say about the future of their own business. If you think about the last, let's say 10, 15, 20 years in advertising in digital, right? Programmatic has really become kind of the primary mechanism for revenue for a lot of these publishers. Right? And so programmatic is a super important part of their business. But, with everything that's happening here with identity now, a lot of these publishers are kind of taking a look in the mirror and thinking about, "Okay, we have an interesting opportunity here to make a decision." And, the decision, the trade off to your question is, Do we continue? Right? Do we put up the login wall? The registration wall, right? Collect that data. And then what do we do with that data? Right? So it's kind of a two-fold process here. Two-step process that they have to make a decision on. First of all, do we hamper the user experience by putting up a registration wall? Will we lose consumers if we do that? Do we create some friction in the process that's not necessary. And if we do, right? We're taking a hit already potentially, to what end? Right? And, I think that's the really interesting question, is to what end? But, what we're starting to see is publishers are saying you know what? Programmatic revenue is super important to us. And so, you know, path one might be: Hey, let's give them this data. Right? Let's give them the authenticated information, the data that we collect. Because if we do, we can continue on with the path that our business has been on. Right? Which is generating this awesome kind of programmatic revenue. Now, alternatively we're starting to see some publishers say hold up. If we say no, if we say: "Hey, we're going to authenticate but we're not going to share the data." Right? Some of the publishers actually view programmatic as almost like the programmatic industrial complex, right? That's almost taken a piece of their business in the last 10, 15, 20 years. Whereas, back in the day, they were selling directly and making all the revenue for themselves, right? And so, some of these publishers are starting to say: You know what? We're not going to play nice with FLOC and Unified ID. And we're going to kind of take some of this back. And what that means in the short term for them, is maybe sacrificing programmatic revenue. But their bet is long-term, maybe some of that money will come back to them direct. Now, that'll probably only be the premium pubs, right? The ones that really feel like they have that leverage and that runway to do something like that. And even so, you know, I'm of the opinion that if certain publishers kind of peel away and do that, that's probably not great for the bigger picture. Even though it might be good for their business. But, you know, let's see what happens. To each business their own >> Yeah. I think the trade-off of monetization and user experience has always been there. Now, more than ever, people want truth. They want trust. And I think the trust factor is huge. And if you're a publisher, you wannna have your audience be instrumental. And I think the big players have sucked out of the audience from the publishers for years. And that's well-documented. People talk about that all the time. I guess the question, it really comes down to is, what alternatives are out there for cookies and which ones do you think will be more successful? Because, I think the consensus is, at least from my reporting and my view, is that the world agrees. Let's make it open. Which one's going to be better? >> Yeah. That's a great question, John. So as I mentioned, right? We have two kinds of work streams here. We've got the walled garden work stream being led by Google and their work around FLOC. And then we've got the open internet, right? Let's say Unified ID 2.0 kind of represents that. I personally don't believe that there is a right answer or an end game here. I don't think that one of them wins over the other, frankly. I think that, you know, first of all, you have those two frameworks. Neither of them are perfect. They're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now, is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution, right? So they're saying, hey we use, you know, an open ID framework in this way to get down to the user level and use that authenticated data. And that's important, but we don't have all the scale. So now we go to a Google and we go to FLOC to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce. Right? We have some of our own data. We have some of our own partnerships. We're going to bring that in and layer it on top, right? And so, really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both with a little extra, you know, something on top. I think that's what we're starting to see out of a lot of companies in the space. And I think that's frankly, where we're headed. >> What do you think the industry will evolve to, in your opinion? Because, I think this is going to be- You can't ignore the big guys on this Obviously the programmatic you mentioned, also the data's there. But, what do you think the market will evolve to with this conundrum? >> So, I think John, where we're headed, you know, I think right now we're having this existential crisis, right? About identity in this industry. Because our world is being turned upside down. All the mechanisms that we've used for years and years are being thrown out the window and we're being told, "Hey, we're going to have new mechanisms." Right? So cookies are going away. Device IDs are going away. And now we've got to come up with new things. And so, the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Everyone's always talking about identity, right? Now, where do I think this is going? If I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today, right? Forget about all the changes. Just think about it now and maybe a few years before today. Identity, for marketers, in my opinion, has been a little bit of a checkbox activity, right? It's been, Hey, Okay. You know, ad tech company or media company. Do you have an identity solution? Okay. Tell me a little bit more about it. Okay. Sounds good. That sounds good. Now, can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business. And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know? Yes, you have it. Okay, great. Let's move on, type of thing, right? And so, that's kind of where we've been. Now, all of a sudden, the cookies are going away. The device IDs are going away. And so the world is turning upside down. We're in this crisis of: how are we going to keep doing what we were doing for the last 10 years in the future? So, everyone's talking about it and we're tryna re-engineer the mechanisms. Now, if I was to look into the crystal ball, right? Two, three years from now, where I think we're headed is, not much is going to change. And what I mean by that, John is, I think that marketers will still go to companies and say, "Do you have an ID solution? Okay, tell me more about it. Okay. Let me understand a little bit better. Okay. You do it this way. Sounds good." Now, the ways in which companies are going to do it will be different. Right now it's FLOC and Unified ID and this and that, right? The ways, the mechanisms will be a little bit different. But, the end state. Right? The actual way in which we operate as an industry and the view of the landscape in my opinion, will be very simple or very similar, right? Because marketers will still view it as a, tell me you have an ID solution, make me feel good about it, help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So, I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment, where we do have to talk about and figure out what we're going to do in the future. My viewpoint is that the future will actually not look all that different than the present. >> And then I'll say the user base is the audience, their data behind it helps create new experiences, machine learning and AI are going to create those. And if you have the data, you're either sharing it or using it. That's what we're finding. Shiv Gupta, great insights. Dropping some nice gems here. Founder of U of Digital and also the adjunct professor of programmatic advertising at Leavey School of business in Santa Clara University. Professor, thank you for coming and dropping the gems here and insight. Thank you. >> Thanks a lot for having me, John. Really appreciate it. >> Thanks for watching The Cookie Conundrum This is theCUBE host, John Furrier, me. Thanks for watching. (uplifting electronic music)

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique