(bright music) >> Hello, everyone. Welcome to theCUBE special presentation of International Women's Day. I'm John Furrier, host of theCUBE. This is a global special open program we're doing every year. We're going to continue it every quarter. We're going to do more and more content, getting the voices out there and celebrating the diversity. And I'm excited to have an amazing guest here, LaDavia Drane, who's the head of Global Inclusion Diversity & Equity at AWS. LaDavia, we tried to get you in on AWS re:Invent, and you were super busy. So much going on. The industry has seen the light. They're seeing everything going on, and the numbers are up, but still not there, and getting better. This is your passion, our passion, a shared passion. Tell us about your situation, your career, how you got into it. What's your story? >> Yeah. Well, John, first of all, thank you so much for having me. I'm glad that we finally got this opportunity to speak. How did I get into this work? Wow, you know, I'm doing the work that I love to do, number one. It's always been my passion to be a voice for the voiceless, to create a seat at the table for folks that may not be welcome to certain tables. And so, it's been something that's been kind of the theme of my entire professional career. I started off as a lawyer, went to Capitol Hill, was able to do some work with members of Congress, both women members of Congress, but also, minority members of Congress in the US Congress. And then, that just morphed into what I think has become a career for me in inclusion, diversity, and equity. I decided to join Amazon because I could tell that it's a company that was ready to take it to the next level in this space. And sure enough, that's been my experience here. So now, I'm in it, I'm in it with two feet, doing great work. And yeah, yeah, it's almost a full circle moment for me. >> It's really an interesting background. You have a background in public policy. You mentioned Capitol Hill. That's awesome. DC kind of moves slow, but it's a complicated machinery there. Obviously, as you know, navigating that, Amazon grew significantly. We've been at every re:Invent with theCUBE since 2013, like just one year. I watched Amazon grow, and they've become very fast and also complicated, like, I won't say like Capitol, 'cause that's very slow, but Amazon's complicated. AWS is in the realm of powering a generation of public policy. We had the JEDI contract controversy, all kinds of new emerging challenges. This pivot to tech was great timing because one, (laughs) Amazon needed it because they were growing so fast in a male dominated world, but also, their business is having real impact on the public. >> That's right, that's right. And when you say the public, I'll just call it out. I think that there's a full spectrum of diversity and we work backwards from our customers, and our customers are diverse. And so, I really do believe, I agree that I came to the right place at the right time. And yeah, we move fast and we're also moving fast in this space of making sure that both internally and externally, we're doing the things that we need to do in order to reach a diverse population. >> You know, I've noticed how Amazon's changed from the culture, male dominated culture. Let's face it, it was. And now, I've seen over the past five years, specifically go back five, is kind of in my mental model, just the growth of female leaders, it's been impressive. And there was some controversy. They were criticized publicly for this. And we said a few things as well in those, like around 2014. How is Amazon ensuring and continuing to get the female employees feel represented and empowered? What's going on there? What programs do you have? Because it's not just doing it, it's continuing it, right? And 'cause there is a lot more to do. I mean, the half (laughs) the products are digital now for everybody. It's not just one population. (laughs) Everyone uses digital products. What is Amazon doing now to keep it going? >> Well, I'll tell you, John, it's important for me to note that while we've made great progress, there's still more that can be done. I am very happy to be able to report that we have big women leaders. We have leaders running huge parts of our business, which includes storage, customer experience, industries and business development. And yes, we have all types of programs. And I should say that, instead of calling it programs, I'm going to call it strategic initiatives, right? We are very thoughtful about how we engage our women. And not only how we hire, attract women, but how we retain our women. We do that through engagement, groups like our affinity groups. So Women at Amazon is an affinity group. Women in finance, women in engineering. Just recently, I helped our Black employee network women's group launch, BEN Women. And so you have these communities of women who come together, support and mentor one another. We have what we call Amazon Circles. And so these are safe spaces where women can come together and can have conversations, where we are able to connect mentors and sponsors. And we're seeing that it's making all the difference in the world for our women. And we see that through what we call Connections. We have an inclusion sentiment tracker. So we're able to ask questions every single day and we get a response from our employees and we can see how are our women feeling, how are they feeling included at work? Are they feeling as though they can be who they are authentically at Amazon? And so, again, there's more work that needs to be done. But I will say that as I look at the data, as I'm talking to engaging women, I really do believe that we're on the right path. >> LaDavia, talk about the urgent needs of the women that you're hearing from the Circles. That's a great program. The affinity circles, the groups are great. Now, you have the groups, what are you hearing? What are the needs of the women? >> So, John, I'll just go a little bit into what's becoming a conversation around equity. So, initially I think we talked a lot about equality, right? We wanted everyone to have fair access to the same things. But now, women are looking for equity. We're talking about not just leveling the playing field, which is equality, but don't give me the same as you give everyone else. Instead, recognize that I may have different circumstances, I may have different needs. And give me what I need, right? Give me what I need, not just the same as everyone else. And so, I love seeing women evolve in this way, and being very specific about what they need more than, or what's different than what a man may have in the same situation because their circumstances are not always the same and we should treat them as such. >> Yeah, I think that's a great equity point. I interviewed a woman here, ex-Amazonian, she's now a GSI, Global System Integrator. She's a single mom. And she said remote work brought her equity because people on her team realized that she was a single mom. And it wasn't the, how do you balance life, it was her reality. And what happened was, she had more empathy with the team because of the new work environment. So, I think this is an important point to call out, that equity, because that really makes things smoother in terms of the interactions, not the assumptions, you have to be, you know, always the same as a man. So, how does that go? What's the current... How would you characterize the progress in that area right now? >> I believe that employers are just getting better at this. It's just like you said, with the hybrid being the norm now, you have an employer who is looking at people differently based on what they need. And it's not a problem, it's not an issue that a single mother says, "Well, I need to be able to leave by 5:00 PM." I think that employers now, and Amazon is right there along with other employers, are starting just to evolve that muscle of meeting the needs. People don't have to feel different. You don't have to feel as though there's some kind of of special circumstance for me. Instead, it's something that we, as employers, we're asking for. And we want to meet those needs that are different in some situations. >> I know you guys do a lot of support of women outside of AWS, and I had a story I recorded for the program. This woman, she talked about how she was a nerd from day one. She's a tomboy. They called her a tomboy, but she always loved robotics. And she ended up getting dual engineering degrees. And she talked about how she didn't run away and there was many signals to her not to go. And she powered through, at that time, and during her generation, that was tough. And she was successful. How are you guys taking the education to STEM, to women, at young ages? Because we don't want to turn people away from tech if they have the natural affinity towards it. And not everyone is going to be, as, you know, (laughs) strong, if you will. And she was a bulldog, she was great. She's just like, "I'm going for it. I love it so much." But not everyone's like that. So, this is an educational thing. How do you expose technology, STEM for instance, and making it more accessible, no stigma, all that stuff? I mean, I think we've come a long way, but still. >> What I love about women is we don't just focus on ourselves. We do a very good job of thinking about the generation that's coming after us. And so, I think you will see that very clearly with our women Amazonians. I'll talk about three different examples of ways that Amazonian women in particular, and there are men that are helping out, but I'll talk about the women in particular that are leading in this area. On my team, in the Inclusion, Diversity & Equity team, we have a program that we run in Ghana where we meet basic STEM needs for a afterschool program. So we've taken this small program, and we've turned their summer camp into this immersion, where girls and boys, we do focus on the girls, can come and be completely immersed in STEM. And when we provide the technology that they need, so that they'll be able to have access to this whole new world of STEM. Another program which is run out of our AWS In Communities team, called AWS Girls' Tech Day. All across the world where we have data centers, we're running these Girls' Tech Day. They're basically designed to educate, empower and inspire girls to pursue a career in tech. Really, really exciting. I was at the Girls' Tech Day here recently in Columbus, Ohio, and I got to tell you, it was the highlight of my year. And then I'll talk a little bit about one more, it's called AWS GetIT, and it's been around for a while. So this is a program, again, it's a global program, it's actually across 13 countries. And it allows girls to explore cloud technology, in particular, and to use it to solve real world problems. Those are just three examples. There are many more. There are actually women Amazonians that create these opportunities off the side of their desk in they're local communities. We, in Inclusion, Diversity & Equity, we fund programs so that women can do this work, this STEM work in their own local communities. But those are just three examples of some of the things that our Amazonians are doing to bring girls along, to make sure that the next generation is set up and that the next generation knows that STEM is accessible for girls. >> I'm a huge believer. I think that's amazing. That's great inspiration. We need more of that. It's awesome. And why wouldn't we spread it around? I want to get to the equity piece, that's the theme for this year's IWD. But before that, getting that segment, I want to ask you about your title, and the choice of words and the sequence. Okay, Global Inclusion, Diversity, Equity. Not diversity only. Inclusion is first. We've had this debate on theCUBE many years now, a few years back, it started with, "Inclusion is before diversity," "No, diversity before inclusion, equity." And so there's always been a debate (laughs) around the choice of words and their order. What's your opinion? What's your reaction to that? Is it by design? And does inclusion come before diversity, or am I just reading it to it? >> Inclusion doesn't necessarily come before diversity. (John laughs) It doesn't necessarily come before equity. Equity isn't last, but we do lead with inclusion in AWS. And that is very important to us, right? And thank you for giving me the opportunity to talk a little bit about it. We lead with inclusion because we want to make sure that every single one of our builders know that they have a place in this work. And so it's important that we don't only focus on hiring, right? Diversity, even though there are many, many different levels and spectrums to diversity. Inclusion, if you start there, I believe that it's what it takes to make sure that you have a workplace where everyone knows you're included here, you belong here, we want you to stay here. And so, it helps as we go after diversity. And we want all types of people to be a part of our workforce, but we want you to stay. And inclusion is the thing. It's the thing that I believe makes sure that people stay because they feel included. So we lead with inclusion. Doesn't mean that we put diversity or equity second or third, but we are proud to lead with inclusion. >> Great description. That was fabulous. Totally agree. Double click, thumbs up. Now let's get into the theme. Embracing equity, 'cause this is a term, it's in quotes. What does that mean to you? You mentioned it earlier, I love it. What does embrace equity mean? >> Yeah. You know, I do believe that when people think about equity, especially non-women think about equity, it's kind of scary. It's, "Am I going to give away what I have right now to make space for someone else?" But that's not what equity means. And so I think that it's first important that we just educate ourselves about what equity really is. It doesn't mean that someone's going to take your spot, right? It doesn't mean that the pie, let's use that analogy, gets smaller. The pie gets bigger, right? >> John: Mm-hmm. >> And everyone is able to have their piece of the pie. And so, I do believe that I love that IWD, International Women's Day is leading with embracing equity because we're going to the heart of the matter when we go to equity, we're going to the place where most people feel most challenged, and challenging people to think about equity and what it means and how they can contribute to equity and thus, embrace equity. >> Yeah, I love it. And the advice that you have for tech professionals out there on this, how do you advise other groups? 'Cause you guys are doing a lot of great work. Other organizations are catching up. What would be your advice to folks who are working on this equity challenge to reach gender equity and other equitable strategic initiatives? And everyone's working on this. Sustainability and equity are two big projects we're seeing in every single company right now. >> Yeah, yeah. I will say that I believe that AWS has proven that equity and going after equity does work. Embracing equity does work. One example I would point to is our AWS Impact Accelerator program. I mean, we provide 30 million for early stage startups led by women, Black founders, Latino founders, LGBTQ+ founders, to help them scale their business. That's equity. That's giving them what they need. >> John: Yeah. >> What they need is they need access to capital. And so, what I'd say to companies who are looking at going into the space of equity, I would say embrace it. Embrace it. Look at examples of what companies like AWS is doing around it and embrace it because I do believe that the tech industry will be better when we're comfortable with embracing equity and creating strategic initiatives so that we could expand equity and make it something that's just, it's just normal. It's the normal course of business. It's what we do. It's what we expect of ourselves and our employees. >> LaDavia, you're amazing. Thank you for spending the time. My final couple questions really more around you. Capitol Hill, DC, Amazon Global Head of Inclusion, Diversity & Equity, as you look at making change, being a change agent, being a leader, is really kind of similar, right? You've got DC, it's hard to make change there, but if you do it, it works, right? (laughs) If you don't, you're on the side of the road. So, as you're in your job now, what are you most excited about? What's on your agenda? What's your focus? >> Yeah, so I'm most excited about the potential of what we can get done, not just for builders that are currently in our seats, but for builders in the future. I tend to focus on that little girl. I don't know her, I don't know where she lives. I don't know how old she is now, but she's somewhere in the world, and I want her to grow up and for there to be no question that she has access to AWS, that she can be an employee at AWS. And so, that's where I tend to center, I center on the future. I try to build now, for what's to come, to make sure that this place is accessible for that little girl. >> You know, I've always been saying for a long time, the software is eating the world, now you got digital transformation, business transformation. And that's not a male only, or certain category, it's everybody. And so, software that's being built, and the systems that are being built, have to have first principles. Andy Jassy is very strong on this. He's been publicly saying, when trying to get pinned down about certain books in the bookstore that might offend another group. And he's like, "Look, we have first principles. First principles is a big part of leading." What's your reaction to that? How would you talk to another professional and say, "Hey," you know this, "How do I make the right call? Am I doing the wrong thing here? And I might say the wrong thing here." And is it first principles based? What's the guardrails? How do you keep that in check? How would you advise someone as they go forward and lean in to drive some of the change that we're talking about today? >> Yeah, I think as leaders, we have to trust ourselves. And Andy actually, is a great example. When I came in as head of ID&E for AWS, he was our CEO here at AWS. And I saw how he authentically spoke from his heart about these issues. And it just aligned with who he is personally, his own personal principles. And I do believe that leaders should be free to do just that. Not to be scripted, but to lead with their principles. And so, I think Andy's actually a great example. I believe that I am the professional in this space at this company that I am today because of the example that Andy set. >> Yeah, you guys do a great job, LaDavia. What's next for you? >> What's next. >> World tour, you traveling around? What's on your plate these days? Share a little bit about what you're currently working on. >> Yeah, so you know, at Amazon, we're always diving deep. We're always diving deep, we're looking for root cause, working very hard to look around corners, and trying to build now for what's to come in the future. And so I'll continue to do that. Of course, we're always planning and working towards re:Invent, so hopefully, John, I'll see you at re:Invent this December. But we have some great things happening throughout the year, and we'll continue to... I think it's really important, as opposed to looking to do new things, to just continue to flex the same muscles and to show that we can be very, very focused and intentional about doing the same things over and over each year to just become better and better at this work in this space, and to show our employees that we're committed for the long haul. So of course, there'll be new things on the horizon, but what I can say, especially to Amazonians, is we're going to continue to stay focused, and continue to get at this issue, and doing this issue of inclusion, diversity and equity, and continue to do the things that work and make sure that our culture evolves at the same time. >> LaDavia, thank you so much. I'll give you the final word. Just share some of the big projects you guys are working on so people can know about them, your strategic initiatives. Take a minute to plug some of the major projects and things that are going on that people either know about or should know about, or need to know about. Take a minute to share some of the big things you guys got going on, or most of the things. >> So, one big thing that I would like to focus on, focus my time on, is what we call our Innovation Fund. This is actually how we scale our work and we meet the community's needs by providing micro grants to our employees so our employees can go out into the world and sponsor all types of different activities, create activities in their local communities, or throughout the regions. And so, that's probably one thing that I would like to focus on just because number one, it's our employees, it's how we scale this work, and it's how we meet our community's needs in a very global way. And so, thank you John, for the opportunity to talk a bit about what we're up to here at Amazon Web Services. But it's just important to me, that I end with our employees because for me, that's what's most important. And they're doing some awesome work through our Innovation Fund. >> Inclusion makes the workplace great. Empowerment, with that kind of program, is amazing. LaDavia Drane, thank you so much. Head of Global Inclusion and Diversity & Equity at AWS. This is International Women's Day. I'm John Furrier with theCUBE. Thanks for watching and stay with us for more great interviews and people and what they're working on. Thanks for watching. (bright music)

(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Hey guys, welcome back to the Cube, the leader in live enterprise and emerging tech coverage. We are live in Las Vegas at MGM Grand Hotel, Lisa Martin with Dave Valante, covering our first time covering Palo Alto Ignite. 22 in person. Dave, we've had some great conversations so far. We've got two days of wall to wall coverage. We're gonna be talking with Palo Alto execs, leaders, customers, partners, and we're gonna be talking about the partner ecosystem >>Next. Wow. Super important. You know, it's funny you talk about for a minute, you didn't know where we were. I, I came to Vegas in May. I feel like I never left two weeks ago reinvent, which was I, I thought the most awesome reinvent ever. And it was really all about the ecosystem and the marketplace. So super excited to have that >>Conversation. Yeah, we've got Wet Whit Krump joining us, director of America's business development worldwide channels and customer programs at AWS marketplace. Wet, welcome to the Cube. Great to have >>You. Thanks for having me. Give >>Us a, you got a big title there. Give us a little bit of flavor of your scope of work at aws. >>Yeah, sure. So I, I've been with the marketplace team now almost eight years and originally founded our channel programs. And my scope has expanded to not just cover channels, but all things related to customers. So if you think about marketplace having sort of two sides, one being very focused on the isv, I tend to manage all things related to our in customer and our, our channel partners. >>What are some of the feedback that you're getting from customers and channel partners as the marketplace has has evolved so much? >>Yeah. You know, it's, it's, it's been interesting to watch over the course of the years, getting to see it start its infancy and grow up. One of the things that we hear often from customers and from our channel partners, and maybe not so directly, is it's not about finding the things they necessarily want to buy, although that's important, but it's the actual act of how they're able to purchase things and making that a much more streamlined process, especially in large enterprises where there's a lot of complexity. We wanna make that a lot simple, simpler for our customers. >>I mean, vendor management is such a hassle, right? But, so when I come into the marketplace, it's all there. I gotta console, it's integrated, I choose what I want. The billing is simplified. How has that capability evolved since the time that you've been at aws and where do you, where do you want to take it? >>Yeah, so when we, we first started Marketplace, it was really a pay as you go model customer come, they buy whatever, you know, whatever the, the whatever the solution was. And then it was, you know, charged by the hour and then the year. And one of the things that we discovered through customer and partner feedback was especially when they're dealing with large enterprise purchases, you know, they want to be able to instantiate those custom price and terms, you know, into that contract while enjoying the benefits of, of marketplace. And that's been, I think the biggest evolution started in 2017 with private offers, 2018 with consulting partner private offers. And then we've added things on over time to streamline procurement for, for >>Customers. So one of the hottest topics right now, everybody wants to talk about the macro and the headwinds and everything else, but when you talk to customers like, look, I gotta do more with less, less, that's the big theme. Yeah. And, and I wanna optimize my spend. Cloud allows me to do that because I can dial down, I can push storage to, to lower tiers. There's a lot of different things that I can do. Yeah. What are the techniques that people are using in the ecosystem Yeah. To bring in the partner cost optimization. Yeah. >>And so one of the key things that, that partners are, are, are doing for customers, they act as that trusted advisor. And, you know, when using marketplace either directly or through a partner, you know, customers are able to really save money through a licensing flexibility. They're also able to streamline their procurement. And then if there's an at-risk spin situation, they're able to, to manage that at-risk spend by combining marketplace and AWS spin into into one, you know, basically draws down their commitments to, to the company. >>And we talk about ask at-risk spend, you might talk about user or lose IT type of spend, right? Yeah. And so you, you increase the optionality in terms of where you can get value from your cloud spend. That's >>All right. Customers are thinking about their, their IT spend more strategically now more than ever. And so they're not just thinking about how do I buy infrastructure here and then software here, data services, they wanna combine this into one place. It's a lot less to keep up with a lot, a lot less overhead for them. But also just the simplification that you alluded to earlier around, you know, all the billing and vendor management is, and now in one, one streamlined, one streamlined process. Talk >>About that as a facilitator of organizations being able to reduce their risk profile. >>Yeah, so, you know, one of the things that, that came out earlier this year with Forrester was a to were total economic impact studies for both an ISV and for the end customer. But there was also a thought leadership study done where they surveyed over 700 customers worldwide to sort of get their thoughts on procurement and risk profile management. And, and one of the things that was really, you know, really surprising was is was that, you know, I guess it was like over 78% of of respondents DEF stated that they didn't feel like their, their companies had a really well-defined governance model and that over half of software and data purchases actually went outside of procurement. And so the companies aren't really able to, don't, they don't really have eyes on all of this spin and it's substantial >>And that's a, a huge risk for the organization. >>Yeah. Huge risk for the organization. And, and you know, half of the respondents stated outright that like they viewed marketplaces a way for them to reduce their risk profile because they, they were able to have a better governance model around that. >>So what's the business case can take us through that. How, how should a customer think about that? So, okay, I get that the procurement department likes it and the CFO probably likes it, but how, what, what's the dynamic around the business? So if I'm a, let's say I'm, I'm a bus, I'm a business person, I'm a, and running the process, I got my little, I get my procurement reach around. Yeah. What does the data suggest that what's in it from me, right? From a company wide standpoint, you know, what are the, maybe the Forester guys address this. So yeah, that overall business case I think is important. >>Yeah, I think, I think one of the big headlines for the end customer is because of license flexibility is that is is about a 10% cost savings in, in license cost. They're able to right size their purchases to buy the things they actually need. They're not gonna have these big overarching ELAs. There's gonna be a lot of other things in there that, that they don't, they don't really aren't gonna really directly use. You're talking about shelfware, you know, that sort of the classic term buy something, it never gets used, you know, also from just a, a getting things done perspective, big piece of feedback from customers is the contracting process takes a long time. It takes several months, especially for a large purchase. And a lot of those discussions are very repetitive. You know, you're talking about the same things over and over again. And we actually built a feature called standardized contract where we talked to a number of customers and ISVs distilled a contract down into a, a largely a set of terms that both sides already agreed to. And it cuts that, that contract time down by 90%. So if you're a legal team in a company, there's only so many of you and you have a lot of things to get done. If you can shave 90% off your time, that that's, that's now you can now work on a lot of other things for the, the corporation. Right. >>A lot of business impact there. You think faster time to value, faster time to market workforce optimization. >>Yeah. Yeah. I mean, it, it, you know, from an ISV standpoint, the measurement is they're, they're able to close deals about 40% faster, which is great for the isv. I mean obviously they love that. But if you're a customer, you're actually getting the innovative technologies you need 40% faster. So you can actually do the work you want to take it to your customers and drive the business. >>You guys recently launched, what is it, vendor Insights? Yeah. Talk a little bit about that, the value. What are some of the things that you're seeing with that? >>Yeah, so that goes into the, the onboarding value add of marketplaces. The number of things that go into, to cutting that time according to Forrester by 75%. But Vendor Insights was based on a key piece, offa impact from customers. So, you know, marketplace is used for, one of the reasons is discoverability by customers, Hey, what is the broader landscape? Look for example of security or storage partners, you know, trying to, trying to understand what is even available. And then the double click is, alright, well how does that company, or how does that vendor fit into my risk profile? You know, understanding what their compliance metrics are, things of that nature. And so historically they would have to, a customer would've to go to an ISV and say, all right, I want you to fill out this form, you know that my questionnaire. And so they would trade this back and forth as they have questions. Now with vendor insights, a customer can actually subscribe to this and they're able to actually see the risk profile of that vendor from the inside out, you know, from the inside of their SaaS application, what does it look like on a real time basis? And they can go back and look at that whenever they want. And you know, the, the, the feedback since the launch has been fantastic. And that, and I think that helps us double down on the already the, the onboarding benefits that we are providing customers. >>This, this, I wanna come back to this idea of cost optimization and, and try to tie it into predictability. You know, a lot of people, you know, complain, oh, I got surprised at the end of the month. So if I understand it wit by, by leveraging the marketplace and the breadth that you have in the marketplace, I can say, okay, look, I'm gonna spend X amount on tech. Yeah. And, and this approach allows me to say, all right, because right now procurement or historically procurement's been a bunch of stove pipes, I can't take from here and easily put it over there. Right. You're saying that this not only addresses the sort of cost optimization, does it also address the predictability challenge? >>Yeah, and I, I think another way to describe that is, is around cost controls. And you know, just from a reporting perspective, you know, we, we have what are called cost utilization reports or curve files. And we provide those to customers anytime they want and they can load those into Tableau, use whatever analysis tools that they want to be able to use. And so, and then you can actually tag usage in those reports. And what we're really talking about is helping customers adopt thin op practices. So, you know, develop directly for the cloud customers are able to understand, okay, who's using what, when and where. So everyone's informed that creates a really collaborative environment. It also holds people accountable for their spin. So that, you know, again, talking about shelfware, we bought things we're not gonna use or we're overusing people are using software that they probably don't really need to. And so that's, that adds to that predictable is everyone has great visibility into what's happening. And there's >>Another, I mean, of course saving money is, is, is in vogue right now because you know, the headwinds and the economics, et cetera. But there's also another side of the equation, which is, I mean, I see this a lot. You know, the CFO says financial people, why is our cloud bill so high? Well it's because we're actually driving all this revenue. And so, you know, you've seen it so many so often in companies, you know, the, the spreadsheet analysis says, oh, cut that. Well, what happens to revenue if you cut that? Right? Yeah. So with that visibility, the answer may be, well actually if we double down on that, yeah, we're actually gonna make more money cuz we actually have a margin on this and it's, it's got operating leverage. So if we double that, you know, we could, so that kind of cross organization communication to make better decisions, I think is another key factor. Yeah. >>Huge impact there. Talk ultimately about how the buyer's journey seems to have been really transformed >>The >>Correct. Right? So if you're, if you're a buyer, you know, initially to your point is, you know, I'm just looking for a point solution, right? And then you move on to the next one and the next one. And now, you know, working with our teams and using the platform, you know, and frankly customers are thinking more strategically about their IT spend holistically. The conversations that we're having with us is, it's not about how do I find the solution today, but here's my forward looking software spend, or I'm going through a migration, I wanna rationalize the software portfolio I have today as I'm gonna lift and shift it to aws. You know, what is going to make the trip? What are we gonna discard entirely because it's not really optimized for the cloud. Or there's that shelf wheel component, which is, hey, you know, maybe 15 to 25% of my portfolio, it's just not even getting utilized. And that, and that's a sunk cost to your point, which is, you know, that's, that's money I could be using on something that really impacts the bottom line in various areas of the business. Right. >>What would you say is the number one request you get or feedback you get from the end customers? And how is that different from what you hear from the channel partners? How aligned or Yeah. Are those >>Vectors? I would say from a customer perspective, one of the key things I hear about is around visibility of spin, right? And I was just talking about these reports and you know, using cost optimization tools, being able to use features like identity and access management, managing entitlements, private marketplaces. Basically them being able to have a stronger governance model in the cloud. For one thing, it's, it's, you know, keeping everybody on track like some of the points I was talking about earlier, but also cost, cost optimization around, you know, limiting vendor sprawl. Are we actually really using all the things that we need? And then from a channel partner perspective, you know, some of the things I talked about earlier about that 40% faster sales cycle, you know, that that TEI or the total economic impact study that was done by Forrester was, was built for the isv. >>But if you're a channel partner sitting between the customer and the isv, you kind of get to, you get a little bit of the best of both worlds, right? You're acting as that, you're acting as that that advisor. And so if you're a channel partner, the procurement streamlining is a huge benefit because the, you know, like you said, saving money is in vogue right now. You're trying to do more with less. So if you're thinking about 20, 27% faster win rates, 40% faster time to close, and you're the customer who's trying to impact the bottom line by, by innovating more, more quickly, those two pieces of feedback are really coming together and meeting in, in the middle >>Throughout 2021, or sorry, 2022, our survey partner, etr Enterprise Technology Research has asked their panel a question is what's your strategy for, you know, doing more with less? By far the number one response has been consolidating redundant vendors. Yes. And then optimizing cloud was, you know, second, but, but way, way lower than that. The number from last survey went from 34%. It's now up to 44% in the January survey, which is in the field, which they gave me a glimpse to last night. So you're seeing dramatic uptick Yeah. In that point. Yeah. And then you guys are helping, >>We, we definitely are. I mean, it, there's the reporting piece so they have a better visibility of what they're doing. And then you think about a, a feature like private marketplace and manage entitlements. So private marketplace enables a customer to create their own private marketplace as the name states where they can limit access to it for certain types of software to the actual in customer who needs to use that software. And so, you know, not everybody needs a license to software X, right? And so that helps with the sprawl comment to your point, that's, that's on the increase, right? Am I actually spending money on things that we need to use? >>But also on the consolidation front, you, we, we talked with nikesh an hour or so ago, he was mentioning on stage, if you, if you just think of this number of security tools or cybersecurity tools that an organization has on its network, 30 to 50. And we were talking about, well, how does Palo Alto Networks what's realistic in terms of consolidation? But it sounds like what you're doing in the marketplace is giving organizations the visibility, correct, for sure. Into what they're running, usage spend, et cetera, to help facilitate ultimately at some point facilitate a strategic consolidation. >>It's, that's exactly right. And if you, you think about cost optimization, our procurement features, you know, the, the practice that we're trying to help customers around, around finops, it's all about helping customers build a, a modern procurement practice and supply chain. And so that helps with, with that point exactly. The keynotes >>Point. Exactly. So last question for you. What, what's next? What can we expect? >>Oh, so what's next for me is, you know, I, I really want to, you know, my channel business for example, you know, I want to think about enabling new types of partners. So if we've worked really heavily with resellers, we worked very heavily with Palo Alto on the reseller community, how are we bringing in more services partners of various types? You know, the gsi, the distributors, cloud service providers, managed security service providers was in a keynote yesterday listening to Palo Alto talk about their five routes to market. And, you know, they had these bubbles. And so I was like, gosh, that's exactly how I'm thinking about the business is how am I expanding my own footprint to customers that have deeper, I mean, excuse me, to partners that have deeper levels of cloud knowledge, can be more of that advisor, help customers really understand how to maximize their business on aws. And, and you know, my job is to really help facilitate that, that innovative technology through those partners. >>So sounds like powerful force, that ecosystem. Exactly. Great alignment. AWS and Palo Alto, thank you so much for joining us with, we >>Appreciate, thanks for having >>With what's going on at aws, the partner network, the mp, and all that good stuff. That's really the value in it for customers, ISVs and channel partners. I like. We appreciate your insights. >>Thank you. Thanks for having me. Thank you. >>Our guests and Dave Valante. I'm Lisa Martin. You're watching the Cube Lee Leer in live enterprise and emerging tech coverage.

>>Good afternoon from the Venetian Expo, center, hall, whatever you wanna call it, in Las Vegas. Lisa Martin here. It's day four. I'm not sure what this place is called. Wait, >>What? >>Lisa Martin here with Dave Ante. This is the cube. This is day four of a ton of coverage that we've been delivering to you, which, you know, cause you've been watching since Monday night, Dave, we are almost at the end, we're almost at the show wrap. Excited to bring back, we've been talking about security, a lot about security. Excited to bring back a, an alumni to talk about that. But what's your final thoughts? >>Well, so just in, in, in the context of security, we've had just three in a row talking about cyber, which is like the most important topic. And I, and I love that we're having Palo Alto Networks on Palo Alto Networks is the gold standard in security. Talk to CISOs, they wanna work with them. And, and it was, it's interesting because I've been following them for a little bit now, watch them move to the cloud and a couple of little stumbling points. But I said at the time, they're gonna figure it out and, and come rocking back. And they have, and the company's just performing unbelievably well despite, you know, all the macro headwinds that we love to >>Talk about. So. Right. And we're gonna be unpacking all of that with one of our alumni. As I mentioned, Anker Shaw is with us, the SVP and GM of Palo Alto Networks. Anker, welcome back to the Cub. It's great to see you. It's been a while. >>It's good to be here after a couple years. Yeah, >>Yeah. I think three. >>Yeah, yeah, for sure. Yeah. Yeah. It's a bit of a blur after Covid. >>Everyone's saying that. Yeah. Are you surprised that there are still this many people on the show floor? Cuz I am. >>I am. Yeah. Look, I am not, this is my fourth, last year was probably one third or one fourth of this size. Yeah. But pre covid, this is what dream went looked like. And it's energizing, it's exciting. It's just good to be doing the good old things. So many people and yeah. Amazing technology and innovation. It's been incredible. >>Let's talk about innovation. I know you guys, Palo Alto Networks recently acquired cyber security. Talk to us a little bit about that. How is it gonna compliment Prisma? Give us all the scoop on that. >>Yeah, for sure. Look, some of the recent, the cybersecurity attacks that we have seen are related to supply chain, the colonial pipeline, many, many supply chain. And the reason for that is the modern software supply chain, not the physical supply chain, the one that AWS announced, but this is the software supply chain is really incredibly complicated, complicated developers that are building and shipping code faster than ever before. And the, the site acquisition at the center, the heart of that was securing the entire supply chain. White House came with a new initiative on supply chain security and SBO software bill of material. And we needed a technology, a company, and a set of people who can really deliver to that. And that's why we acquired that for supply chain security, otherwise known as cicd, security, c >>IDC security. Yeah. So how will that complement PRIs McCloud? >>Yeah, so look, if you look at our history lease over the last four years, we have been wanting to, our mission mission has been to build a single code to cloud platform. As you may know, there are over 3000 security vendors in the industry. And we said enough is enough. We need a platform player who can really deliver a unified cohesive platform solution for our customers because they're sick and tired of buying PI point product. So our mission has been to deliver that code to cloud platform supply chain security was a missing piece and we acquired them, it fits right really nicely into our portfolio of products and solution that customers have. And they'll have a single pin of glass with this. >>Yeah. So there's a lot going on. You've got, you've got an adversary that is incredibly capable. Yeah. These days and highly motivated and extremely sophisticated mentioned supply chain. It's caused a shift in, in CSO strategies, talking about the pandemic, of course we know work from home that changed things. You've mentioned public policy. Yeah. And, and so, and as well you have the cloud, cloud, you know, relatively new. I mean, it's not that new, but still. Yeah. But you've got the shared responsibility model and not, not only do you have the shared responsibility model, you have the shared responsibility across clouds and OnPrem. So yes, the cloud helps with security, but that the CISO has to worry about all these other things. The, the app dev team is being asked to shift left, you know, secure and they're not security pros. Yeah. And you know, kind audit is like the last line of defense. So I love this event, I love the cloud, but customers need help in making their lives simpler. Yeah. And the cloud in and of itself, because, you know, shared responsibility doesn't do that. Yeah. That's what Palo Alto and firms like yours come in. >>Absolutely. So look, Jim, this is a unable situation for a lot of the Cisco, simply because there are over 26 million developers, less than 3 million security professional. If you just look at all the announcement the AWS made, I bet you there were like probably over 2000 features. Yeah. I mean, they're shipping faster than ever before. Developers are moving really, really fast and just not enough security people to keep up with the velocity and the innovation. So you are right, while AWS will guarantee securing the infrastructure layer, but everything that is built on top of it, the new machine learning stuff, the new application, the new supply chain applications that are developed, that's the responsibility of the ciso. They stay up at night, they don't know what's going on because developers are bringing new services and new technology. And that's why, you know, we've always taken a platform approach where customers and the systems don't have to worry about it. >>What AWS new service they have, it's covered, it's secured. And that's why the adopters, McCloud and Palo Alto Networks, because regardless what developers bring, security is always there by their side. And so security teams need just a simple one click solution. They don't have to worry about it. They can sleep at night, keep the bad actors away. And, and that's, that's where Palo Alto Networks has been innovating in this area. AWS is one of our biggest partners and you know, we've integrated with, with a lot of their services. We launch about three integrations with their services. And we've been doing this historically for more and >>More. Are you still having conversations with the security folks? Or because security is a board level conversation, are your conversations going up a stack because this is a C-suite problem, this is a board level initiative? >>Absolutely. Look, you know, there was a time about four years ago, like the best we could do is director of security. Now it's just so CEO level conversation, board level conversation to your point, simply because I mean, if, if all your financial stuff is going to public cloud, all your healthcare data, all your supply chain data is going to public cloud, the board is asking very simple question, what are you doing to secure that? And to be honest, the question is simple. The answer's not because all the stuff that we talked about, too many applications, lots and lots of different services, different threat vectors and the bad actors, the bad guys are always a step ahead of the curve. And that's why this has become a board level conversation. They wanna make sure that things are secure from the get go before, you know, the enterprises go too deep into public cloud adoption. >>I mean there, there was shift topics a little bit. There was hope or kinda early this year that that cyber was somewhat insulated from the sort of macro press pressures. Nobody's safe. Even the cloud is sort of, you know, facing those, those headwinds people optimizing costs. But one thing when you talk to customers is, I always like to talk about that, that optiv graph. We've all seen it, right? And it's just this eye test of tools and it's a beautiful taxonomy, but there's just too many tools. So we're seeing a shift from point tools to platforms because obviously a platform play, and that's a way. So what are you seeing in the, in the field with customers trying to optimize their infrastructure costs with regard to consolidating to >>Platforms? Yeah. Look, you rightly pointed out one thing, the cybersecurity industry in general and Palo Alto networks, knock on wood, the stocks doing well. The macro headwinds hasn't impacted the security spend so far, right? Like time will tell, we'll, we'll see how things go. And one of the primary reason is that when you know the economy starts to slow down, the customers again want to invest in platforms. It's simple to deploy, simple to operationalize. They want a security partner of choice that knows that they, it's gonna be by them through the entire journey from code to cloud. And so that's why platform, especially times like these are more important than they've ever been before. You know, customers are investing in the, the, the product I lead at Palo Alto network called Prisma Cloud. It's in the cloud network application protection platform seen app space where once again, customers that investing in platform from quote to cloud and avoiding all the point products for sure. >>Yeah. Yeah. And you've seen it in, in Palo Alto's performance. I mean, not every cyber firm has is, is, >>You know, I know. Ouch. CrowdStrike Yeah. >>Was not. Well you saw that. I mean, and it was, and and you know, the large customers were continuing to spend, it was the small and mid-size businesses Yeah. That were, were were a little bit soft. Yeah. You know, it's a really, it's really, I mean, you see Okta now, you know, after they had some troubles announcing that, you know, their, their, their visibility's a little bit better. So it's, it's very hard to predict right now. And of course if TOMA Brava is buying you, then your stock price has been up and steady. That's, >>Yeah. Look, I think the key is to have a diversified portfolio of products. Four years ago before our CEO cash took over the reins of the company, we were a single product X firewall company. Right. And over time we have added XDR with the first one to introduce that recently launched x Im, you know, to, to make sure we build an NextGen team, cloud security is a completely net new investment, zero trust with access as workers started working remotely and they needed to make sure enterprises needed to make sure that they're accessing the applications securely. So we've added a lot of portfolio products over time. So you have to remain incredibly diversified, stay strong, because there will be stuff like remote work that slowed down. But if you've got other portfolio product like cloud security, while those secular tailwinds continue to grow, I mean, look how fast AWS is growing. 35, 40%, like $80 billion run rate. Crazy at that, that scale. So luckily we've got the portfolio of products to ensure that regardless of what the customer's journey is, macro headwinds are, we've got portfolio of solutions to help our customers. >>Talk a little bit about the AWS partnership. You talked about the run rate and I was reading a few days ago. You're right. It's an 82 billion arr, massive run rate. It's crazy. Well, what are, what is a Palo Alto Networks doing with aws and what's the value in it to help your customers on a secure digital transformation journey? >>Well, absolutely. We have been doing business with aws. We've been one of their security partners of choice for many years now. We have a presence in the marketplace where customers can through one click deploy the, the several Palo Alto Networks security solutions. So that's available. Like I said, we had launch partner to many, many new products and innovation that AWS comes up with. But always the day one partner, Adam was talking about some of those announcements and his keynote security data lake was one of those. And they were like a bunch of others related to compute and others. So we have been a partner for a long time, and look, AWS is an incredibly customer obsessed company. They've got their own security products. But if the customer says like, Hey, like I'd like to pick this from yours, but there's three other things from Palo Alto Networks or S MacCloud or whatever else that may be, they're open to it. And that's the great thing about AWS where it doesn't have to be wall garden open ecosystem, let the customer pick the best. >>And, and that's, I mean, there's, there's examples where AWS is directly competitive. I mean, my favorite example is Redshift and Snowflake. I mean those are directly competitive products, but, but Snowflake is an unbelievably great relationship with aws. They do cyber's, I think different, I mean, yeah, you got guard duty and you got some other stuff there. But generally speaking, the, correct me if I'm wrong, the e the ecosystem has more room to play on AWS than it may on some other clouds. >>A hundred percent. Yeah. Once again, you know, guard duty for examples, we've got a lot of customers who use guard duty and Prisma Cloud and other Palo Alto Networks products. And we also ingest the data from guard duty. So if customers want a single pane of glass, they can use the best of AWS in terms of guard duty threat detection, but leverage other technology suite from, you know, a platform provider like Palo Alto Networks. So you know, that that, you know, look, world is a complicated place. Some like blue, some like red, whatever that may be. But we believe in giving customers that choice, just like AWS customers want that. Not a >>Problem. And at least today they're not like directly, you know, in your space. Yeah. You know, and even if they were, you've got such a much mature stack. Absolutely. And my, my frankly Microsoft's different, right? I mean, you see, I mean even the analysts were saying that some of the CrowdStrike's troubles for, cuz Microsoft's got the good enough, right? So >>Yeah. Endpoint security. Yeah. And >>Yeah, for sure. So >>Do you have a favorite example of a customer where Palo Alto Networks has really helped them come in and, and enable that secure business transformation? Anything come to mind that you think really shines a light on Palo Alto Networks and what it's able to do? >>Yeah, look, we have customers across, and I'm gonna speak to public cloud in general, right? Like Palo Alto has over 60,000 customers. So we've been helping with that business transformation for years now. But because it's reinvented aws, the Prisma cloud product has been helping customers across different industry verticals. Some of the largest credit card processing companies, they can process transactions because we are running security on top of the workloads, the biggest financial services, biggest healthcare customers. They're able to put the patient health records in public cloud because Palo Alto Networks is helping them get there. So we are helping accelerated that digital journey. We've been an enabler. Security is often perceived as a blocker, but we have always treated our role as enabler. How can we get developers and enterprises to move as fast as possible? And like, my favorite thing is that, you know, moving fast and going digital is not a monopoly of just a tech company. Every company is gonna be a tech company Oh absolutely. To public cloud. Yes. And we want to help them get there. Yeah. >>So the other thing too, I mean, I'll just give you some data. I love data. I have a, ETR is our survey partner and I'm looking at Data 395. They do a survey every quarter, 1,250 respondents on this survey. 395 were Palo Alto customers, fortune 500 s and P 500, you know, big global 2000 companies as well. Some small companies. Single digit churn. Yeah. Okay. Yeah. Very, very low replacement >>Rates. Absolutely. >>And still high single digit new adoption. Yeah. Right. So you've got that tailwind going for you. Yeah, >>Right. It's, it's sticky because especially our, our main business firewall, once you deploy the firewall, we are inspecting all the network traffic. It's just so hard to rip and replace. Customers are getting value every second, every minute because we are thwarting attacks from public cloud. And look, we, we, we provide solutions not just product, we just don't leave the product and ask the customers to deploy it. We help them with deployment consumption of the product. And we've been really fortunate with that kind of gross dollar and netten rate for our customers. >>Now, before we wrap, I gotta tease, the cube is gonna be at Palo Alto Ignite. Yeah. In two weeks back here. I think we're at D mgm, right? We >>Were at D MGM December 13th and >>14th. So give us a little, show us a little leg if you would. What could we expect? >>Hey, look, I mean, a lot of exciting new things coming. Obviously I can't talk about it right now. The PR Inc is still not dry yet. But lots of, lots of new innovation across our three main businesses. Network security, public cloud, security, as well as XDR X. Im so stay tuned. You know, you'll, you'll see a lot of new exciting things coming up. >>Looking forward to it. >>We are looking forward to it. Last question on curf. You, if you had a billboard to place in New York Times Square. Yeah. You're gonna take over the the the Times Square Nasdaq. What does the billboard say about why organizations should be working with Palo Alto Networks? Yeah. To really embed security into their dna. Yeah. >>You know when Jim said Palo Alto Networks is the gold standard for security, I thought it was gonna steal it. I think it's pretty good gold standard for security. But I'm gonna go with our mission cyber security partner's choice. We want to be known as that and that's who we are. >>Beautifully said. Walker, thank you so much for joining David in the program. We really appreciate your insights, your time. We look forward to seeing you in a couple weeks back here in Vegas. >>Absolutely. Can't have enough of Vegas. Thank you. Lisa. >>Can't have in Vegas, >>I dunno about that. By this time of the year, I think we can have had enough of Vegas, but we're gonna be able to see you on the cubes coverage, which you could catch up. Palo Alto Networks show Ignite December, I believe 13th and 14th on the cube.net. We want to thank Anker Shaw for joining us. For Dave Ante, this is Lisa Martin. You're watching the Cube, the leader in live enterprise and emerging tech coverage.

>>Hello, brilliant humans and welcome back to Las Vegas, Nevada, where we are live from the AWS Reinvent Show floor here with the cube. My name is Savannah Peterson, joined with Dave Valante, and we have a very exciting conversation with you. Two, two companies you may have heard of. We've got AWS and Red Hat in the house. Manu and Joel, thank you so much for being here. Love this little fist bump. Started off, that's right. Before we even got rolling, Manu, you said that you wanted this to be the best segment of, of the cubes airing. We we're doing over a hundred segments, so you're gonna have to bring the heat. >>We're ready. We're did go. Are we ready? Yeah, go. We're ready. Let's bring it on. >>We're ready. All right. I'm, I'm ready. Dave's ready. Let's do it. How's the show going for you guys real quick before we dig in? >>Yeah, I think after Covid, it's really nice to see that we're back into the 2019 level and, you know, people just want to get out, meet people, have that human touch with each other, and I think a lot of trust gets built as a functional that, so it's super amazing to see our partners and customers here at Reedman. Yeah, >>And you've got a few in the house. That's true. Just a few maybe, maybe a couple >>Very few shows can say that, by the way. Yeah, it's maybe a handful. >>I think one of the things we were saying, it's almost like the entire Silicon Valley descended in the expo hall area, so >>Yeah, it's >>For a few different reasons. There's a few different silicon defined. Yeah, yeah, yeah. Don't have strong on for you. So far >>It's, it's, it is amazing. It's the 10th year, right? It's decade, I think I've been to five and it's, it grows every single year. It's the, you have to be here. It's as simple as that. And customers from every single industry are here too. You don't get, a lot of shows have every single industry and almost every single location around the globe. So it's, it's a must, must be >>Here. Well, and the personas evolved, right? I was at reinvent number two. That was my first, and it was all developers, not all, but a lot of developers. And today it's a business mix, really is >>Totally, is a business mix. And I just, I've talked about it a little bit down the show, but the diversity on the show floor, it's the first time I've had to wait in line for the ladies' room at a tech conference. Almost a two decade career. It is, yeah. And it was really refreshing. I'm so impressed. So clearly there's a commitment to community, but also a commitment to diversity. Yeah. And, and it's brilliant to see on the show floor. This is a partnership that is robust and has been around for a little while. Money. Why don't you tell us a little bit about the partnership here? >>Yes. So Red Hand and AWS are best friends, you know, forever together. >>Aw, no wonder we got the fist bumps and all the good vibes coming out. I know, it's great. I love that >>We have a decade of working together. I think the relationship in the first phase was around running rail bundled with E two. Sure. We have about 70,000 customers that are running rail, which are running mission critical workloads such as sap, Oracle databases, bespoke applications across the state of verticals. Now, as more and more enterprise customers are finally, you know, endorsing and adopting public cloud, I think that business is just gonna continue to grow. So a, a lot of progress there. The second titration has been around, you know, developers tearing Red Hat and aws, Hey, listen, we wanna, it's getting competitive. We wanna deliver new features faster, quicker, we want scale and we want resilience. So just entire push towards devs containers. So that's the second chapter with, you know, red Hat OpenShift on aws, which launched as a, a joint manage service in 2021 last year. And I think the third phase, which you're super excited about, is just bringing the ease of consumption, one click deployment, and then having our customers, you know, benefit from the joint committed spend programs together. So, you know, making sure that re and Ansible and JBoss, the entire portfolio of Red Hat products are available on AWS marketplace. So that's the 1, 2, 3, it of our relationship. It's a decade of working together and, you know, best friends are super committed to making sure our customers and partners continue successful. >>Yeah, that he said it, he said it perfectly. 2008, I know you don't like that, but we started with Rel on demand just in 2008 before E two even had a console. So the partnership has been there, like Manu says, for a long time, we got the partnership, we got the products up there now, and we just gotta finalize that, go to market and get that gas on the fire. >>Yeah. So Graviton Outpost, local zones, you lead it into all the new stuff. So that portends, I mean, 2008, we're talking two years after the launch of s3. >>That's right. >>Right. So, and now look, so is this a harbinger of things to come with these new innovations? >>Yeah, I, I would say, you know, the innovation is a key tenant of our partnership, our relationship. So if you look at from a product standpoint, red Hat or Rel was one of the first platforms that made a support for graviton, which is basically 40% better price performance than any other distribution. Then that translated into making sure that Rel is available on all of our regions globally. So this year we launched Switzerland, Spain, India, and Red Hat was available on launch there, support for Nitro support for Outpost Rosa support on Outpost as well. So I think that relationship, that innovation on the product side, that's pretty visible. I think that innovation again then translates into what we are doing on marketplace with one click deployments we spoke about. I think the third aspect of the know innovation is around making sure that we are making our partners and our customers successful. So one of the things that we've done so far is Joe leads a, you know, a black belt team that really goes into each customer opportunity, making sure how can we help you be successful. We launched and you know, we should be able to share that on a link. After this, we launched like a big playlist, which talks about every single use case on how do you get successful and running OpenShift on aws. So that innovation on behalf of our customers partners to make them successful, that's been a key tenant for us together as >>Well. That's right. And that team that Manu is talking about, we're gonna, gonna 10 x that team this year going into January. Our fiscal yield starts in January. Love that. So yeah, we're gonna have a lot of no hiring freeze over here. Nope. No ma'am. No. Yeah, that's right. Yeah. And you know what I love about working with aws and, and, and Manu just said it very, all of that's customer driven. Every single event that we, that he just talked about in that timeline, it's customer driven, right? Customers wanted rail on demand, customers want JBoss up in the cloud, Ansible this week, you know, everything's up there now. So it's just getting that go to market tight and we're gonna, we're gonna get that done. >>So what's the algorithm for customer driven in terms of taking the input? Because if every customers saying, Hey, I this a >>Really similar >>Question right up, right? I, that's what I want. And if you know, 95% of the customers say it, Jay, maybe that's a good idea. >>Yeah, that's right. Trends. But >>Yeah. You know, 30% you might be like, mm, you know, 20%, you know, how do you guys decide when to put gas on the fire? >>No, that, I think, as I mentioned, there are about 70,000 large customers that are running rail on Easy Two, many of these customers are informing our product strategy. So we have, you know, close to about couple of thousand power users. We have customer advisory booths, and these are the, you know, customers are informing us, Hey, let's get all of the Red Hat portfolio and marketplace support for graviton, support for Outpost. Why don't we, why are we not able to dip into the consumption committed spend programs for both Red Hat and aws? That's right. So it's these power users both at the developer level as well as the guys who are actually doing large commercial consumption. They are the ones who are informing the roadmap for both Red Hat and aws. >>But do, do you codify the the feedback? >>Yeah, I'm like, I wanna see the database, >>The, I think it was, I don't know, it was maybe Chasy, maybe it was Besos, that that data beats intuition. So do you take that information and somehow, I mean, it's global, 70,000 customers, right? And they have different weights, different spending patterns, different levels of maturity. Yeah. Do you, how do you codify that and then ultimately make the decision? Yeah, I >>If, I mean, well you, you've got the strategic advisory boards, which are made up of customers and partners and you know, you get, you get a good, you gotta get a good slice of your customer base to get, and you gotta take their feedback and you gotta do something with it, right? That's the, that's the way we do it and codify it at the product level, I'm sure open source. That's, that's basically how we work at the product level, right? The most elegant solution in open source wins. And that's, that's pretty much how we do that at the, >>I would just add, I think it's also just the implicit trust that the two companies had built with each other, working in the trenches, making our customers and partners successful over the last decade. And Alex, give an example. So that manifests itself in context of like, you know, Amazon and Red Hat just published the entire roadmap for OpenShift. What are the new features that are becoming over the next six to nine to 12 months? It's open source available on GitHub. Customers can see, and then they can basically come back and give feedback like, Hey, you know, we want hip compliance. We just launched. That was a big request that was coming from our >>Customers. That is not any process >>Also for Graviton or Nvidia instances. So I I I think it's a, >>Here's the thing, the reason I'm pounding on this is because you guys have a pretty high hit rate, and I think as a >>Customer, mildly successful company >>As, as a customer advocate, the better, you know, if, if you guys make bets that pay off, it's gonna pay off for customers. Right. And because there's a lot of failures in it. Yeah. I mean, let's face it. That's >>Right. And I think, I think you said the key word bets. You place a lot of small bets. Do you have the, the innovation engine to do that? AWS is the perfect place to place those small bets. And then you, you know, pour gas on the fire when, when they take off. >>Yeah, it's a good point. I mean, it's not expensive to experiment. Yeah. >>Especially in the managed service world. Right? >>And I know you love taking things to market and you're a go to market guy. Let's talk gtm, what's got your snow pumped about GTM for 2023? >>We, we are gonna, you know, 10 x the teams that's gonna be focused on these products, right? So we're gonna also come out with a hybrid committed spend program for our customers that meet them where they want to go. So they're coming outta the data center going into a cloud. We're gonna have a nice financial model for them to do that. And that's gonna take a lot of the friction out. >>Yeah. I mean, you've nailed it. I, I think the, the fact that now entire Red Hat portfolio is available on marketplace, you can do it on one click deployment. It's deeply integrated with Amazon services and the most important part that Joel was making now customers can double dip. They can drive benefit from the consumption committed spend programs, both from Red Hat and from aws, which is amazing. Which is a game changer That's right. For many of our large >>Customers. That's right. And that, so we're gonna, we're gonna really go to town on that next year. That's, and all the, all the resources that I have, which are the technology sellers and the sas, you know, the engineers we're growing this team the most out that team. So it's, >>When you say 10 x, how many are you at now? I'm >>Curious to see where you're headed. Tell you, okay. There's not right? Oh no, there's not one. It's triple digit. Yeah, yeah. >>Today. Oh, sweet. Awesome. >>So, and it's a very sizable team. They're actually making sure that each of our customers are successful and then really making sure that, you know, no customer left behind policy. >>And it's a great point that customers love when Amazonians and Red Hats show up, they love it and it's, they want to get more of it, and we're gonna, we're gonna give it to 'em. >>Must feel great to be loved like that. >>Yeah, that's right. Yeah. Yeah. I would say yes. >>Seems like it's safe to say that there's another decade of partnership between your two companies. >>Hope so. That's right. That's the plan. >>Yeah. And I would say also, you know, just the IBM coming into the mix here. Yeah. I, you know, red Hat has informed the way we have turned around our partnership with ibm, essentially we, we signed the strategic collaboration agreement with the company. All of IBM software now runs on Rosa. So that is now also providing a lot of tailwinds both to our rail customers and as well as Rosa customers. And I think it's a very net creative, very positive for our partnership. >>That's right. It's been very positive. Yep. Yeah. >>You see the >>Billboards positive. Yeah, right. Also that, that's great. Great point, Dave. Yep. We have a, we have a new challenge, a new tradition on the cube here at Reinvent where we're, well, it's actually kind of a glamor moment for you, depending on how you leverage it. We're looking for your 32nd hot take your Instagram reel, your sizzle thought leadership, biggest takeaway, most important theme from this year's show. I know you want, right, Joel? I mean, you TM boy, I feel like you can spit the time. >>Yeah. It is all about Rosa for us. It is all in on that, that's the native OpenShift offering on aws and that's, that's the soundbite we're going go to town with. Now, I don't wanna forget all the other products that are in there, but Rosa is a, is a very key push for us this year. >>Fantastic. All right. Manu. >>I think our customers, it's getting super competitive. Our customers want to innovate just a >>Little bit. >>The enterprise customers see the cloud native companies. I wanna do what these guys are doing. I wanna develop features at a fast clip. I wanna scale, I wanna be resilient. And I think that's really the spirit that's coming out. So to Joel's point, you know, move to worlds containers, serverless, DevOps, which was like, you know, aha, something that's happening on the side of an enterprise is not becoming mainstream. The business is demanding it. The, it is becoming the centerpiece in the business strategy. So that's been really like the aha. Big thing that's happening here. >>Yeah. And those architectures are coming together, aren't they? That's correct. Right. You know, VMs and containers, it used to be one architecture and then at the other end of the spectrum is serverless. People thought of those as different things and now it's a single architecture and, and it's kind of right approach for the right job. >>And, and a compliments say to Red Hat, they do an incredible job of hiding that complexity. Yeah. Yes. And making sure that, you know, for example, just like, make it easier for the developers to create value and then, and you know, >>Yeah, that's right. Those, they were previously siloed architectures and >>That's right. OpenShift wanna be place where you wanna run containers or virtual machines. We want that to be this Yeah. Single place. Not, not go bolt on another piece of architecture to just do one or the other. Yeah. >>And hey, the hybrid cloud vision is working for ibm. No question. You know, and it's achievable. Yeah. I mean, I just, I've said unlike, you know, some of the previous, you know, visions on fixing the world with ai, hybrid cloud is actually a real problem that you're attacking and it's showing the results. Agreed. Oh yeah. >>Great. Alright. Last question for you guys. Cause it might be kind of fun, 10 years from now, oh, we're at another, we're sitting here, we all look the same. Time has passed, but we are not aging, which is a part of the new technology that's come out in skincare. That's my, I'm just throwing that out there. Why not? What do you guys hope that you can say about the partnership and, and your continued commitment to community? >>Oh, that's a good question. You go first this time. Yeah. >>I think, you know, the, you know, for looking into the future, you need to look into the past. And Amazon has always been driven by working back from our customers. That's like our key tenant, principle number 1 0 1. >>Couple people have said that on this stage this week. Yeah. >>Yeah. And I think our partnership, I hope over the next decade continues to keep that tenant as a centerpiece. And then whatever comes out of that, I think we, we are gonna be, you know, working through that. >>Yeah. I, I would say this, I think you said that, well, the customer innovation is gonna lead us to wherever that is. And it's, it's, it's gonna be in the cloud for sure. I think we can say that in 10 years. But yeah, anything from, from AI to the quant quantum computing that IBM's really pushing behind that, you know, those are, those are gonna be things that hopefully we show up on a, on a partnership with Manu in 10 years, maybe sooner. >>Well, whatever happens next, we'll certainly be covering it here on the cube. That's right. Thank you both for being here. Joel Manu, fantastic interview. Thanks to see you guys. Yeah, good to see you brought the energy. I think you're definitely ranking high on the top interviews. We >>Love that for >>The day. >>Thank >>My pleasure >>Job, guys. Now that you're competitive at all, and thank you all for tuning in to our live coverage here from AWS Reinvent in Las Vegas, Nevada, with Dave Valante. I'm Savannah Peterson. You're watching The Cube, the leading source for high tech coverage.

(upbeat music) >> Hello, everyone and welcome back to fabulous Las Vegas, Nevada, where we are here on the show floor at AWS re:Invent. We are theCUBE. I am Savannah Peterson, joined with John Furrier. John, afternoon, day two, we are in full swing. >> Yes. >> What's got you most excited? >> Just got lunch, got the food kicking in. No, we don't get coffee. (Savannah laughing) >> Way to bring the hype there, John. >> No, there's so many people here just in Amazon. We're back to 2019 levels of crowd. The interest levels are high. Next gen, cloud security, big part of the keynote. This next segment, I am super excited about. CUBE Alumni, going back to 2013, 10 years ago he was on theCUBE. Now, 10 years later we're at re:Invent, looking forward to this guest and it's about security, great topic. >> I don't want to delay us anymore, please welcome Mark. Mark, thank you so much for being here with us. Massive day for you and the team. I know you oversee three different units at Amazon, Inspector, Detective, and the most recently announced, Security Lake. Tell us about Amazon Security Lake. >> Well, thanks Savannah. Thanks John for having me. Well, Security Lake has been in the works for a little bit of time and it got announced today at the keynote as you heard from Adam. We're super excited because there's a couple components that are really unique and valuable to our customers within Security Lake. First and foremost, the foundation of Security Lake is an open source project we call OCFS, Open Cybersecurity Framework Schema. And what that allows is us to work with the vendor community at large in the security space and develop a language where we can all communicate around security data. And that's the language that we put into Security Data Lake. We have 60 vendors participating in developing that language and partnering within Security Lake. But it's a communal lake where customers can bring all of their security data in one place, whether it's generated in AWS, they're on-prem, or SaaS offerings or other clouds, all in one location in a language that allows analytics to take advantage of that analytics and give better outcomes for our customers. >> So Adams Selipsky big keynote, he spent all the bulk of his time on data and security. Obviously they go well together, we've talked about this in the past on theCUBE. Data is part of security, but this security's a little bit different in the sense that the global footprint of AWS makes it uniquely positioned to manage some security threats, EKS protection, a very interesting announcement, runtime layer, but looking inside and outside the containers, probably gives extra telemetry on some of those supply chains vulnerabilities. This is actually a very nuanced point. You got Guard Duty kind of taking its role. What does it mean for customers 'cause there's a lot of things in this announcement that he didn't have time to go into detail. Unpack all the specifics around what the security announcement means for customers. >> Yeah, so we announced four items in Adam's keynote today within my team. So I'll start with Guard Duty for EKS runtime. It's complimenting our existing capabilities for EKS support. So today Inspector does vulnerability assessment on EKS or container images in general. Guard Duty does detections of EKS workloads based on log data. Detective does investigation and analysis based on that log data as well. With the announcement today, we go inside the container workloads. We have more telemetry, more fine grain telemetry and ultimately we can provide better detections for our customers to analyze risks within their container workload. So we're super excited about that one. Additionally, we announced Inspector for Lambda. So Inspector, we released last year at re:Invent and we focused mostly on EKS container workloads and EC2 workloads. Single click automatically assess your environment, start generating assessments around vulnerabilities. We've added Lambda to that capability for our customers. The third announcement we made was Macy sampling. So Macy has been around for a while in delivering a lot of value for customers providing information around their sensitive data within S3 buckets. What we found is many customers want to go and characterize all of the data in their buckets, but some just want to know is there any sensitive data in my bucket? And the sampling feature allows the customer to find out their sensitive data in the bucket, but we don't have to go through and do all of the analysis to tell you exactly what's in there. >> Unstructured and structured data. Any data? >> Correct, yeah. >> And the fourth? >> The fourth, Security Data Lake? (John and Savannah laughing) Yes. >> Okay, ocean theme. data lake. >> Very complimentary to all of our services, but the unique value in the data lake is that we put the information in the customer's control. It's in their S3 bucket, they get to decide who gets access to it. We've heard from customers over the years that really have two options around gathering large scale data for security analysis. One is we roll our own and we're security engineers, we're not data engineers. It's really hard for them to build these distributed systems at scale. The second one is we can pick a vendor or a partner, but we're locked in and it's in their schemer and their format and we're there for a long period of time. With Security Data Lake, they get the best of both worlds. We run the infrastructure at scale for them, put the data in their control and they get to decide what use case, what partner, what tool gives them the most value on top of their data. >> Is that always a good thing to give the customers too much control? 'Cause you know the old expression, you give 'em a knife they play with and they they can cut themselves, I mean. But no, seriously, 'cause what's the provisions around that? Because control was big part of the governance, how do you manage the security? How does the customer worry about, if I have too much control, someone makes a mistake? >> Well, what we finding out today is that many customers have realized that some of their data has been replicated seven times, 10 times, not necessarily maliciously, but because they have multiple vendors that utilize that data to give them different use cases and outcomes. It becomes costly and unwieldy to figure out where all that data is. So by centralizing it, the control is really around who has access to the data. Now, ultimately customers want to make those decisions and we've made it simple to aggregate this data in a single place. They can develop a home region if they want, where all the data flows into one region, they can distribute it globally. >> They're in charge. >> They're in charge. But the controls are mostly in the hands of the data governance person in the company, not the security analyst. >> So I'm really curious, you mentioned there's 60 AWS partner companies that have collaborated on the Security lake. Can you tell us a little bit about the process? How long does it take? Are people self-selecting to contribute to these projects? Are you cherry picking? What does that look like? >> It's a great question. There's three levels of collaboration. One is around the open source project that we announced at Black Hat early in this year called OCSF. And that collaboration is we've asked the vendor community to work with us to build a schema that is universally acceptable to security practitioners, not vendor specific and we've asked. >> Savannah: I'm sorry to interrupt you, but is this a first of its kind? >> There's multiple schemes out there developed by multiple parties. They've been around for multiple years, but they've been built by a single vendor. >> Yeah, that's what I'm drill in on a little bit. It sounds like the first we had this level of collaboration. >> There's been collaborations around them, but in a handful of companies. We've really gone to a broad set of collaborators to really get it right. And they're focused around areas of expertise that they have knowledge in. So the EDR vendors, they're focused around the scheme around EDR. The firewall vendors are focused around that area. Certainly the cloud vendors are in their scope. So that's level one of collaboration and that gets us the level playing field and the language in which we'll communicate. >> Savannah: Which is so important. >> Super foundational. Then the second area is around producers and subscribers. So many companies generate valuable security data from the tools that they run. And we call those producers the publishers and they publish the data into Security Lake within that OCSF format. Some of them are in the form of findings, many of them in the form of raw telemetry. Then the second one is in the subscriber side and those are usually analytic vendors, SIM vendors, XDR vendors that take advantage of the logs in one place and generate analytic driven outcomes on top of that, use cases, if you will, that highlight security risks or issues for customers. >> Savannah: Yeah, cool. >> What's the big customer focus when you start looking at Security Lakes? How do you see that planning out? You said there's a collaboration, love the open source vibe on that piece, what data goes in there? What's sharing? 'Cause a big part of the keynote I heard today was, I heard clean rooms, I've cut my antenna up. I'd love to hear that. That means there's an implied sharing aspect. The security industry's been sharing data for a while. What kind of data's in that lake? Give us an example, take us through. >> Well, this a number of sources within AWS, as customers run their workloads in AWS. We've identified somewhere around 25 sources that will be natively single click into Amazon Security Lake. We were announcing nine of them. They're traditional network logs, BBC flow, cloud trail logs, firewall logs, findings that are generated across AWS, EKS audit logs, RDS data logs. So anything that customers run workloads on will be available in data lake. But that's not limited to AWS. Customers run their environments hybridly, they have SaaS applications, they use other clouds in some instances. So it's open to bring all that data in. Customers can vector it all into this one single location if they decide, we make it pretty simple for them to do that. Again, in the same format where outcomes can be generated quickly and easily. >> Can you use the data lake off on premise or it has to be in an S3 in Amazon Cloud? >> Today it's in S3 in Amazon. If we hear customers looking to do something different, as you guys know, we tend to focus on our customers and what they want us to do, but they've been pretty happy about what we've decided to do in this first iteration. >> So we got a story about Silicon Angle. Obviously the ingestion is a big part of it. The reporters are jumping in, but the 53rd party sources is a pretty big number. Is that coming from the OCSF or is that just in general? Who's involved? >> Yeah, OCSF is the big part of that and we have a list of probably 50 more that want to join in part of this. >> The other big names are there, Cisco, CrowdStrike, Peloton Networks, all the big dogs are in there. >> All big partners of AWS, anyway, so it was an easy conversation and in most cases when we started having the conversation, they were like, "Wow, this has really been needed for a long time." And given our breadth of partners and where we sit from our customers perspective in the center of their cloud journey that they've looked at us and said, "You guys, we applaud you for driving this." >> So Mark, take us through the conversations you're having with the customers at re:Inforce. We saw a lot of meetings happening. It was great to be back face to face. You guys have been doing a lot of customer conversation, security Data Lake came out of that. What was the driving force behind it? What were some of the key concerns? What were the challenges and what's now the opportunity that's different? >> We heard from our customers in general. One, it's too hard for us to get all the data we need in a single place, whether through AWS, the industry in general, it's just too hard. We don't have those resources to data wrangle that data. We don't know how to pick schema. There's multiple ones out there. Tell us how we would do that. So these three challenges came out front and center for every customer. And mostly what they said is our resources are limited and we want to focus those resources on security outcomes and we have security engines. We don't want to focus them on data wrangling and large scale distributed systems. Can you help us solve that problem? And it came out loud and clear from almost every customer conversation we had. And that's where we took the challenge. We said, "Okay, let's build this data layer." And then on top of that we have services like Detective and Guard Duty, we'll take advantage of it as well. But we also have a myriad of ISV third parties that will also sit on top of that data and render out. >> What's interesting, I want to get your reaction. I know we don't have much time left, but I want to get your thoughts. When I see Security Data Lake, which is awesome by the way, love the focus, love how you guys put that together. It makes me realize the big thing in re:Invent this year is this idea of specialized solutions. You got instances for this and that, use cases that require certain kind of performance. You got the data pillars that Adam laid out. Are we going to start seeing more specialized data lakes? I mean, we have a video data lake. Is there going to be a FinTech data lake? Is there going to be, I mean, you got the Great Lakes kind of going on here, what is going on with these lakes? I mean, is that a trend that Amazon sees or customers are aligning to? >> Yeah, we have a couple lakes already. We have a healthcare lake and a financial lake and now we have a security lake. Foundationally we have Lake Formation, which is the tool that anyone can build a lake. And most of our lakes run on top of Lake Foundation, but specialize. And the specialization is in the data aggregation, normalization, enridgement, that is unique for those use cases. And I think you'll see more and more. >> John: So that's a feature, not a bug. >> It's a feature, it's a big feature. The customers have ask for it. >> So they want roll their own specialized, purpose-built data thing, lake? They can do it. >> And customer don't want to combine healthcare information with security information. They have different use cases and segmentation of the information that they care about. So I think you'll see more. Now, I also think that you'll see where there are adjacencies that those lakes will expand into other use cases in some cases too. >> And that's where the right tools comes in, as he was talking about this ETL zero, ETL feature. >> It be like an 80, 20 rule. So if 80% of the data is shared for different use cases, you can see how those lakes would expand to fulfill multiple use cases. >> All right, you think he's ready for the challenge? Look, we were on the same page. >> Okay, we have a new challenge, go ahead. >> So think of it as an Instagram Reel, sort of your hot take, your thought leadership moment, the clip we're going to come back to and reference your brilliance 10 years down the road. I mean, you've been a CUBE veteran, now CUBE alumni for almost 10 years, in just a few weeks it'll be that. What do you think is, and I suspect, I think I might know your answer to this, so feel free to be robust in this. But what do you think is the biggest story, key takeaway from the show this year? >> We're democratizing security data within Security Data Lake for sure. >> Well said, you are our shortest answer so far on theCUBE and I absolutely love and respect that. Mark, it has been a pleasure chatting with you and congratulations, again, on the huge announcement. This is such an exciting day for you all. >> Thank you Savannah, thank you John, pleasure to be here. >> John: Thank you, great to have you. >> We look forward to 10 more years of having you. >> Well, maybe we don't have to wait 10 years. (laughs) >> Well, more years, in another time. >> I have a feeling it'll be a lot of security content this year. >> Yeah, pretty hot theme >> Very hot theme. >> Pretty odd theme for us. >> Of course, re:Inforce will be there this year again, coming up 2023. >> All the res. >> Yep, all the res. >> Love that. >> We look forward to see you there. >> All right, thanks, Mark. >> Speaking of res, you're the reason we are here. Thank you all for tuning in to today's live coverage from AWS re:Invent. We are in Las Vegas, Nevada with John Furrier. My name is Savannah Peterson. We are theCUBE and we are the leading source for high tech coverage. (upbeat music)

>>Good morning fellow nerds and welcome back to AWS Reinvent. We are live from the show floor here in Las Vegas, Nevada. My name is Savannah Peterson, joined with my fabulous co-host John Furrier. Day two keynotes are rolling. >>Yeah. What do you thinking this? This is the day where everything comes, so the core gets popped off the bottle, all the announcements start flowing out tomorrow. You hear machine learning from swee lot more in depth around AI probably. And then developers with Verner Vos, the CTO who wrote the seminal paper in in early two thousands around web service that becames. So again, just another great year of next level cloud. Big discussion of data in the keynote bulk of the time was talking about data and business intelligence, business transformation easier. Is that what people want? They want the easy button and we're gonna talk a lot about that in this segment. I'm really looking forward to this interview. >>Easy button. We all want the >>Easy, we want the easy button. >>I love that you brought up champagne. It really feels like a champagne moment for the AWS community as a whole. Being here on the floor feels a bit like the before times. I don't want to jinx it. Our next guest, Scott Castle, from Si Sense. Thank you so much for joining us. How are you feeling? How's the show for you going so far? Oh, >>This is exciting. It's really great to see the changes that are coming in aws. It's great to see the, the excitement and the activity around how we can do so much more with data, with compute, with visualization, with reporting. It's fun. >>It is very fun. I just got a note. I think you have the coolest last name of anyone we've had on the show so far, castle. Oh, thank you. I'm here for it. I'm sure no one's ever said that before, but I'm so just in case our audience isn't familiar, tell us about >>Soy Sense is an embedded analytics platform. So we're used to take the queries and the analysis that you can power off of Aurora and Redshift and everything else and bring it to the end user in the applications they already know how to use. So it's all about embedding insights into tools. >>Embedded has been a, a real theme. Nobody wants to, it's I, I keep using the analogy of multiple tabs. Nobody wants to have to leave where they are. They want it all to come in there. Yep. Now this space is older than I think everyone at this table bis been around since 1958. Yep. How do you see Siente playing a role in the evolution there of we're in a different generation of analytics? >>Yeah, I mean, BI started, as you said, 58 with Peter Lu's paper that he wrote for IBM kind of get became popular in the late eighties and early nineties. And that was Gen one bi, that was Cognos and Business Objects and Lotus 1 23 think like green and black screen days. And the way things worked back then is if you ran a business and you wanted to get insights about that business, you went to it with a big check in your hand and said, Hey, can I have a report? And they'd come back and here's a report. And it wasn't quite right. You'd go back and cycle, cycle, cycle and eventually you'd get something. And it wasn't great. It wasn't all that accurate, but it's what we had. And then that whole thing changed in about two, 2004 when self-service BI became a thing. And the whole idea was instead of going to it with a big check in your hand, how about you make your own charts? >>And that was totally transformative. Everybody started doing this and it was great. And it was all built on semantic modeling and having very fast databases and data warehouses. Here's the problem, the tools to get to those insights needed to serve both business users like you and me and also power users who could do a lot more complex analysis and transformation. And as the tools got more complicated, the barrier to entry for everyday users got higher and higher and higher to the point where now you look, look at Gartner and Forester and IDC this year. They're all reporting in the same statistic. Between 10 and 20% of knowledge workers have learned business intelligence and everybody else is just waiting in line for a data analyst or a BI analyst to get a report for them. And that's why the focus on embedded is suddenly showing up so strong because little startups have been putting analytics into their products. People are seeing, oh my, this doesn't have to be hard. It can be easy, it can be intuitive, it can be native. Well why don't I have that for my whole business? So suddenly there's a lot of focus on how do we embed analytics seamlessly? How do we embed the investments people make in machine learning in data science? How do we bring those back to the users who can actually operationalize that? Yeah. And that's what Tysons does. Yeah. >>Yeah. It's interesting. Savannah, you know, data processing used to be what the IT department used to be called back in the day data processing. Now data processing is what everyone wants to do. There's a ton of data we got, we saw the keynote this morning at Adam Lesky. There was almost a standing of vision, big applause for his announcement around ML powered forecasting with Quick Site Cube. My point is people want automation. They want to have this embedded semantic layer in where they are not having all the process of ETL or all the muck that goes on with aligning the data. All this like a lot of stuff that goes on. How do you make it easier? >>Well, to be honest, I, I would argue that they don't want that. I think they, they think they want that, cuz that feels easier. But what users actually want is they want the insight, right? When they are about to make a decision. If you have a, you have an ML powered forecast, Andy Sense has had that built in for years, now you have an ML powered forecast. You don't need it two weeks before or a week after in a report somewhere. You need it when you're about to decide do I hire more salespeople or do I put a hundred grand into a marketing program? It's putting that insight at the point of decision that's important. And you don't wanna be waiting to dig through a lot of infrastructure to find it. You just want it when you need it. What's >>The alternative from a time standpoint? So real time insight, which is what you're saying. Yep. What's the alternative? If they don't have that, what's >>The alternative? Is what we are currently seeing in the market. You hire a bunch of BI analysts and data analysts to do the work for you and you hire enough that your business users can ask questions and get answers in a timely fashion. And by the way, if you're paying attention, there's not enough data analysts in the whole world to do that. Good luck. I am >>Time to get it. I really empathize with when I, I used to work for a 3D printing startup and I can, I have just, I mean, I would call it PTSD flashbacks of standing behind our BI guy with my list of queries and things that I wanted to learn more about our e-commerce platform in our, in our marketplace and community. And it would take weeks and I mean this was only in 2012. We're not talking 1958 here. We're talking, we're talking, well, a decade in, in startup years is, is a hundred years in the rest of the world life. But I think it's really interesting. So talk to us a little bit about infused and composable analytics. Sure. And how does this relate to embedded? Yeah. >>So embedded analytics for a long time was I want to take a dashboard I built in a BI environment. I wanna lift it and shift it into some other application so it's close to the user and that is the right direction to go. But going back to that statistic about how, hey, 10 to 20% of users know how to do something with that dashboard. Well how do you reach the rest of users? Yeah. When you think about breaking that up and making it more personalized so that instead of getting a dashboard embedded in a tool, you get individual insights, you get data visualizations, you get controls, maybe it's not even actually a visualization at all. Maybe it's just a query result that influences the ordering of a list. So like if you're a csm, you have a list of accounts in your book of business, you wanna rank those by who's priorities the most likely to churn. >>Yeah. You get that. How do you get that most likely to churn? You get it from your BI system. So how, but then the question is, how do I insert that back into the application that CSM is using? So that's what we talk about when we talk about Infusion. And SI started the infusion term about two years ago and now it's being used everywhere. We see it in marketing from Click and Tableau and from Looker just recently did a whole launch on infusion. The idea is you break this up into very small digestible pieces. You put those pieces into user experiences where they're relevant and when you need them. And to do that, you need a set of APIs, SDKs, to program it. But you also need a lot of very solid building blocks so that you're not building this from scratch, you're, you're assembling it from big pieces. >>And so what we do aty sense is we've got machine learning built in. We have an LQ built in. We have a whole bunch of AI powered features, including a knowledge graph that helps users find what else they need to know. And we, we provide those to our customers as building blocks so that they can put those into their own products, make them look and feel native and get that experience. In fact, one of the things that was most interesting this last couple of couple of quarters is that we built a technology demo. We integrated SI sensee with Office 365 with Google apps for business with Slack and MS teams. We literally just threw an Nlq box into Excel and now users can go in and say, Hey, which of my sales people in the northwest region are on track to meet their quota? And they just get the table back in Excel. They can build charts of it and PowerPoint. And then when they go to their q do their QBR next week or week after that, they just hit refresh to get live data. It makes it so much more digestible. And that's the whole point of infusion. It's bigger than just, yeah. The iframe based embedding or the JavaScript embedding we used to talk about four or five years >>Ago. APIs are very key. You brought that up. That's gonna be more of the integration piece. How does embedable and composable work as more people start getting on board? It's kind of like a Yeah. A flywheel. Yes. What, how do you guys see that progression? Cause everyone's copying you. We see that, but this is a, this means it's standard. People want this. Yeah. What's next? What's the, what's that next flywheel benefit that you guys coming out with >>Composability, fundamentally, if you read the Gartner analysis, right, they, when they talk about composable, they're talking about building pre-built analytics pieces in different business units for, for different purposes. And being able to plug those together. Think of like containers and services that can, that can talk to each other. You have a composition platform that can pull it into a presentation layer. Well, the presentation layer is where I focus. And so the, so for us, composable means I'm gonna have formulas and queries and widgets and charts and everything else that my, that my end users are gonna wanna say almost minority report style. If I'm not dating myself with that, I can put this card here, I can put that chart here. I can set these filters here and I get my own personalized view. But based on all the investments my organization's made in data and governance and quality so that all that infrastructure is supporting me without me worrying much about it. >>Well that's productivity on the user side. Talk about the software angle development. Yeah. Is your low code, no code? Is there coding involved? APIs are certainly the connective tissue. What's the impact to Yeah, the >>Developer. Oh. So if you were working on a traditional legacy BI platform, it's virtually impossible because this is an architectural thing that you have to be able to do. Every single tool that can make a chart has an API to embed that chart somewhere. But that's not the point. You need the life cycle automation to create models, to modify models, to create new dashboards and charts and queries on the fly. And be able to manage the whole life cycle of that. So that in your composable application, when you say, well I want chart and I want it to go here and I want it to do this and I want it to be filtered this way you can interact with the underlying platform. And most importantly, when you want to use big pieces like, Hey, I wanna forecast revenue for the next six months. You don't want it popping down into Python and writing that yourself. >>You wanna be able to say, okay, here's my forecasting algorithm. Here are the inputs, here's the dimensions, and then go and just put it somewhere for me. And so that's what you get withy sense. And there aren't any other analytics platforms that were built to do that. We were built that way because of our architecture. We're an API first product. But more importantly, most of the legacy BI tools are legacy. They're coming from that desktop single user, self-service, BI environment. And it's a small use case for them to go embedding. And so composable is kind of out of reach without a complete rebuild. Right? But with SI senses, because our bread and butter has always been embedding, it's all architected to be API first. It's integrated for software developers with gi, but it also has all those low code and no code capabilities for business users to do the minority report style thing. And it's assemble endless components into a workable digital workspace application. >>Talk about the strategy with aws. You're here at the ecosystem, you're in the ecosystem, you're leading product and they have a strategy. We know their strategy, they have some stuff, but then the ecosystem goes faster and ends up making a better product in most of the cases. If you compare, I know they'll take me to school on that, but I, that's pretty much what we report on. Mongo's doing a great job. They have databases. So you kind of see this balance. How are you guys playing in the ecosystem? What's the, what's the feedback? What's it like? What's going on? >>AWS is actually really our best partner. And the reason why is because AWS has been clear for many, many years. They build componentry, they build services, they build infrastructure, they build Redshift, they build all these different things, but they need, they need vendors to pull it all together into something usable. And fundamentally, that's what Cient does. I mean, we didn't invent sequel, right? We didn't invent jackal or dle. These are not, these are underlying analytics technologies, but we're taking the bricks out of the briefcase. We're assembling it into something that users can actually deploy for their use cases. And so for us, AWS is perfect because they focus on the hard bits. The the underlying technologies we assemble those make them usable for customers. And we get the distribution. And of course AWS loves that. Cause it drives more compute and it drives more, more consumption. >>How much do they pay you to say that >>Keynote, >>That was a wonderful pitch. That's >>Absolutely, we always say, hey, they got a lot of, they got a lot of great goodness in the cloud, but they're not always the best at the solutions and that they're trying to bring out, and you guys are making these solutions for customers. Yeah. That resonates with what they got with Amazon. For >>Example, we, last year we did a, a technology demo with Comprehend where we put comprehend inside of a semantic model and we would compile it and then send it back to Redshift. And it takes comprehend, which is a very cool service, but you kind of gotta be a coder to use it. >>I've been hear a lot of hype about the semantic layer. What is, what is going on with that >>Semantec layer is what connects the actual data, the tables in your database with how they're connected and what they mean so that a user like you or me who's saying I wanna bar chart with revenue over time can just work with revenue and time. And the semantic layer translates between what we did and what the database knows >>About. So it speaks English and then they converts it to data language. It's >>Exactly >>Right. >>Yeah. It's facilitating the exchange of information. And, and I love this. So I like that you actually talked about it in the beginning, the knowledge map and helping people figure out what they might not know. Yeah. I, I am not a bi analyst by trade and I, I don't always know what's possible to know. Yeah. And I think it's really great that you're doing that education piece. I'm sure, especially working with AWS companies, depending on their scale, that's gotta be a big part of it. How much is the community play a role in your product development? >>It's huge because I'll tell you, one of the challenges in embedding is someone who sees an amazing experience in outreach or in seismic. And to say, I want that. And I want it to be exactly the way my product is built, but I don't wanna learn a lot. And so you, what you want do is you want to have a community of people who have already built things who can help lead the way. And our community, we launched a new version of the SES community in early 2022 and we've seen a 450% growth in the c in that community. And we've gone from an average of one response, >>450%. I just wanna put a little exclamation point on that. Yeah, yeah. That's awesome. We, >>We've tripled our organic activity. So now if you post this Tysons community, it used to be, you'd get one response maybe from us, maybe from from a customer. Now it's up to three. And it's continuing to trend up. So we're, it's >>Amazing how much people are willing to help each other. If you just get in the platform, >>Do it. It's great. I mean, business is so >>Competitive. I think it's time for the, it's time. I think it's time. Instagram challenge. The reels on John. So we have a new thing. We're gonna run by you. Okay. We just call it the bumper sticker for reinvent. Instead of calling it the Instagram reels. If we're gonna do an Instagram reel for 30 seconds, what would be your take on what's going on this year at Reinvent? What you guys are doing? What's the most important story that you would share with folks on Instagram? >>You know, I think it's really what, what's been interesting to me is the, the story with Redshift composable, sorry. No, composable, Redshift Serverless. Yeah. One of the things I've been >>Seeing, we know you're thinking about composable a lot. Yes. Right? It's, it's just, it's in there, it's in your mouth. Yeah. >>So the fact that Redshift Serverless is now kind becoming the defacto standard, it changes something for, for my customers. Cuz one of the challenges with Redshift that I've seen in, in production is if as people use it more, you gotta get more boxes. You have to manage that. The fact that serverless is now available, it's, it's the default means it now people are just seeing Redshift as a very fast, very responsive repository. And that plays right into the story I'm telling cuz I'm telling them it's not that hard to put some analysis on top of things. So for me it's, it's a, maybe it's a narrow Instagram reel, but it's an >>Important one. Yeah. And that makes it better for you because you get to embed that. Yeah. And you get access to better data. Faster data. Yeah. Higher quality, relevant, updated. >>Yep. Awesome. As it goes into that 80% of knowledge workers, they have a consumer great expectation of experience. They're expecting that five ms response time. They're not waiting 2, 3, 4, 5, 10 seconds. They're not trained on theola expectations. And so it's, it matters a lot. >>Final question for you. Five years out from now, if things progress the way they're going with more innovation around data, this front end being very usable, semantic layer kicks in, you got the Lambda and you got serverless kind of coming in, helping out along the way. What's the experience gonna look like for a user? What's it in your mind's eye? What's that user look like? What's their experience? >>I, I think it shifts almost every role in a business towards being a quantitative one. Talking about, Hey, this is what I saw. This is my hypothesis and this is what came out of it. So here's what we should do next. I, I'm really excited to see that sort of scientific method move into more functions in the business. Cuz for decades it's been the domain of a few people like me doing strategy, but now I'm seeing it in CSMs, in support people and sales engineers and line engineers. That's gonna be a big shift. Awesome. >>Thank >>You Scott. Thank you so much. This has been a fantastic session. We wish you the best at si sense. John, always pleasure to share the, the stage with you. Thank you to everybody who's attuning in, tell us your thoughts. We're always eager to hear what, what features have got you most excited. And as you know, we will be live here from Las Vegas at reinvent from the show floor 10 to six all week except for Friday. We'll give you Friday off with John Furrier. My name's Savannah Peterson. We're the cube, the the, the leader in high tech coverage.

>>Hi, I'm John Ferry with the Cube. We're here for a special exclusive conversation with David Geria, the CEO of Mongo MongoDB. Well established leading platform. It's been around for, I mean, decades. So continues to become the platform of choice for high performance data. This modern data stack that's emerging, a big part of the story here at a reinvent 2022 on top of an already performing a cloud with, you know, chips and silicon specialized instances, the world's gonna be getting faster, smaller, higher performance, lower cost specialized. Dave, thanks for taking the time with me today, >>John. It's great to be here. Thank you for having me. >>Do you see yourself as a ISV or you just go with that, because that's kind of a nomenclature >>When, when I think of the term isv, I think of the notion of someone building an end solution for customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies of the world trying to transform their business or startups who are trying to disrupt either existing industries or create new ones. And so that's, and, and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. The reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. >>So, you know, things like charting no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workloads on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long >>Db. You know, you guys are a feature partner of aws and I would speculate, I don't know if you can comment on this, but I would imagine that you probably produce a lot of revenue for Amazon because you really can't turn off EC two when you do a database work. So, you know, you kind of crank it all the time. You guys are a top partner. How long have you guys been a partner with aws? What's the relationship? >>The relationship's been strong, actually, Amazon spoke at one of our first user conferences in 2013. And since then we've been working together. We've been at reinvent since essentially 2015. And we've been a premier partner, an Emerald sponsor for the last Nu you know, I think four or five years. And so we're very committed to the relationship and I think there's some things that we have a lot, we have a lot of things in common. We care a lot about customers and for us, our customers, our developers, we care a lot about removing friction from their day to day work to move, be able to move fast and be able to, in order to seize new opportunities and respond to new threats. And so consequently, I think the partnership, obviously by nature of our, our common objectives has really come together. >>Talk about the journey of Mongo. I mean, you look back at the history, I, you go back the old lamp stack days, right? So you know, the day developer traction is just really kind of stuck at the none. I mean, it's, it's really well known. And I remember over the conversations, Dave Mongo doesn't scale. I mean, every year we heard something along those lines cuz it just kept scaling. I heard the same thing with AWS back in 2013 timeframe. You, oh, it's just, it's really not for a real prime time. It's, it's for hobbyists, not so much builders, maybe startup cloud, but that developer traction is translated. Can you take us through the journey of Mongo where it is now and, and kinda look back and, and, and take us through what's the state of the art now, >>Right? So just for those of you who, who, those, you know, those in your audience who don't know too much about Mon Be I'll just, you know, start with the background. The company was astounded by developers. It was basically the CTO and some key developers from Double Click who really saw the challenges and the limitations of the relational database architecture because they're trying to serve billions of ads per day and they constantly need to work on the constraints and relational database. And so they essentially decided, why don't we just build a database that we'd want to use? And that was a catalyst to starting MongoDB. The first thing they focused on was, rather than having a tabler data structure, they focused on a document data structure. Why documents? Because there's much more natural and intuitive to work with data and documents in terms of you can set parent child relationships and how you just think about the relationship with data is much more natural in a document than trying to connect data in a, you know, in hundreds of different tables. >>And so that enabled developers to just move so much faster. The second thing they focused on was building a truly distributed architecture, not kind of some adjunct, you know, you know, architecture that maybe made the existing architecture a little bit more scalable. They really took from the ground up a truly distributed architecture. So where you can do native replication, you can do charting and you can do it on a global basis. And so that was the, the other profound, you know, thing that they did. And then since then, what we've also done is, you know, the document model is truly a super set of other models. So we enabled other capabilities like search you can do joins, so you can do very transaction intensive use case among be where fully asset compliant. So you have the highest forms of data guarantees you can do very sophisticated things like time series, you can do device synchronization, you can do real time analytics because we can carve off read only nodes to be able to read and query data in real time rather than have to offload that data into a data warehouse. >>And so that enables developers to just build a wide variety of, of application longing to be, and they get one unified developer interface. It's highly elegant and seamless. And so essentially the cost and tax of matching multiple point tools goes away when, when I think of the term isv, I think of the notion of someone building an end solution for a customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies in the world trying to transform their business or startups or trying to disrupt either existing industries or create new ones. And so that's, and and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. >>Yeah, we're seeing a lot of activity on the Atlas. Do you see yourself as a ISV or you just go with that because that's kind of a nomenclature? >>No, we don't view ourselves as ISV at all. We view ourselves as a developer data platform. And the reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. So, you know, things like sharding, no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workflows on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long ndb. >>You know, the cloud adoption really is putting a lot of pressure on these systems and you're seeing companies in the ecosystem and AWS stepping up, you guys are doing great job, but we're seeing a lot more acceleration around it, on staying on premise for certain use cases. Yet you got the cloud as well growing for workloads and, and you get this hybrid steady state as an operational mode. I call that 10 of the classic cloud adoption track record. You guys are an example of multiple iterations in cloud. You're doing a lot more, we're starting to see this tipping point with others and customers coming kind of on that same pattern. Building platforms on top of aws on top of the primitives, more horsepower, higher level services, industry specific capabilities with data. I mean this is a new kind of cloud, kind of a next generation, you knows next gen you got the classic high performance infrastructure, it's getting better and better, but now you've got this new application platform, you know, reminds me of the old asp, you know, if you will. I mean, so are you seeing customers doing things differently? Can you share your, your reaction to this role of, you know, this new kind of SaaS platform that just isn't an application, it's, it's more, it's deeper than that. What's going on here? We call it super cloud, but >>Like what? Yeah, so essentially what what, you know, a lot of our customers doing, and by the way we have over 37,000 customers of all shapes and sizes from the largest companies in the world to cutting edge startups who are building applications among B, why do they choose MongoDB? Because essentially it's the, you know, the fastest way to innovate and the reason it's the fastest way to innovate is because they can work with data so much easier than working with data on other types of architecture. So the document model is profoundly a breakthrough way to work with data to make it very, very easy. So customers are essentially building these modern applications, you know, applications built on microservices, event driven architectures, you know, addressing sophisticated use cases like time series to, and then ultimately now they're getting into machine learning. We have a bunch of companies building machine learning applications on top of MongoDB. And the reason they're doing that is because one, they get the benefits of being able to, you know, build and work with, with data so much easier than any other platform. And it's highly scale and performant in a way that no other platform is. So literally they can run their, you know, workloads both locally and one, you know, autonomous zone or they can basically be or available zone or they could be basically, you know, anywhere in the world. And we also offer multicloud capabilities, which I can get into later. >>Let's talk about the performance side. I know I was speaking with some Amazon folks every year it's the same story. They're really working on the physics, they're getting the chips, they wanna squeeze as much energy out of that. I've never met a developer that said they wanna run their workload on a slower platform or slower hardware. We know said no developer, right? No one wants to do that. >>Correct. >>So you guys have a lot of experience tuning in with Graviton instances, we're seeing a lot more AWS EC two instances, we're seeing a lot more kind of integrated end to end stories. Data is now security, it's tied into data stacks or data modern kind of data hybrid stack. A lot going on around the hardware performance specialization, the role of data, kind of a modern data stack emerging. What, what's your thoughts on the that that Yeah, >>I, I think if you had asked me, you know, when the cloud started going vogue, like you know, the, you know, the, the later part of the last decade and told me, you know, sitting here 12, 15 years later, would you know, would we be talking about, you know, chip processing speeds? I'd probably thought, nah, we would've moved on by then. But what's really clear is that customers, to your point, customers care about performance, they care about price performance, right? So AWS's investments in Graviton, we have actually deployed a significant portion of our at fleet on Amazon now runs on Graviton. You know, they've built other chip sets like train and, and inferential for like, you know, training models and running inferences. They're doing things like Nitro. And so what that really speaks to is that the cloud providers are focusing on the price performance of their, as you call it, their primitives and their infrastructure and the infrastructure layer that are still very, very important. >>And, and you know, if you look at their revenue, about 60 to 70% of the revenue comes from that pure infrastructure. So to your point, they can't offer a second class solution and still win. So given that now they're seeing a lot of competition from Azure, Azure's building their own chip sets, Google's already obviously doing that and and building specialized chip sets for machine learning. You're seeing these cloud providers compete. So they have to really compete to make their platform the most performant, the most price competitive in the marketplace. Which gives us a great platform to build on to enable developers to build these incredibly highly performant applications that customers are now demand. >>I think that's a really great point. I mean, you know, it's so funny Dave, because you know, I remember those, we don't talk speeds and feeds anymore. We're not talking about boxes. I mean that's old kind of school thinking because it was a data center mentality, speeds and feeds and that was super important. But we're kind of coming back to that in the cloud now in distributed architecture, as you put your platforms out there for developers, you have to run fast. You gotta, you can't give the developer subpar or any kind of performance that's, they'll, they'll go somewhere else. I mean that's the reality of what developers, no one, again, no one says I wanna go on the slower platform unless it's some sort of policy based on price or some sort of thing. But, but for the most part it's gotta run fast. So you got the tail of two clouds going on here, you got Amazon classic ias, keep making it faster under the hood. >>And then you got the new abstraction layers of the higher level services. That's where you guys are bridging this new, new generational shift where it's like, hey, you know what? I can go, I can run a headless application, I can run a SAS app that's refactored with data. So you've seen a lot more innovation with developers, you know, running stuff in, in the C I C D pipeline that was once it, and you're seeing security and data operations kind of emerging as a structural change of how companies are, are are transforming on the business side. What's your reaction to that business transformation and the role of the developer? >>Right, so I mean I have to obviously give amazing kudos to the, you know, to AWS and the Amazon team for what they've built. Obviously they're the ones who kind of created the cloud industry and they continue to push the innovation in the space. I mean today they have over 300 services and you know, obviously, you know, no star today is building anything not on the cloud because they have so many building blocks to start with. But what we though have found from our talking to our customers is that in some ways there is still, you know, the onus is on the customer to figure out which building block to use to be able to stitch together the applications and solutions they wanna build. And what we have done is taken essentially an opinionated point of view and said we will enable you to do that. >>You know, using one data model. You know, Amazon today offers I think 17 or 18 different types of databases. We don't think like, you know, having a tool for every job makes sense because over time the tax and cost of learning, managing and supporting those different applications just don't make a lot of sense or just become cost prohibitive. And so we think offering one data model, one, you know, elegant user experience, you know, one way to address the broadest set of of use cases is that we think is a better way. But clearly customers have choice. They can use Amazon's primitives and those second layer services as you as you described, or they can use us. Unfortunately we've seen a lot of customers come to us with our approach and so does Amazon. And I have to give obviously again kudos and Amazon is very customer obsessed and so we have a great relationship with them, both technically in terms of the product integrations we do as well as working with 'em in the field, you know, on joint customer opportunities. >>Speaking of, while you mentioned that, I wanna just ask you, how is that marketplace relationship going with aws? Some of the partners are really seeing great economic and joint selling or them selling your, your stuff. So there's a real revenue pop there in that religion. Can you comment on that? >>So we had been working the partner in the marketplace for many years now, more from a field point of view where customers could leverage their existing commitments to AWS and leverage essentially, you know, using Atlas and applying in an atlas towards their commits. There was also some sales incentives for people in the field to basically work together so that, you know, everyone won should we collectively win a customer? What we recently announced is as pay as you Go initiative, where literally a customer on the Amazon marketplace can basically turn up, you know, an Alice instance with no commitment. So it's so easy. So we're just pushing the envelope to just reduce the friction for people to use Atlas on aws. And it's working really very well. The uptake has been been very strong and and we feel like we're just getting started because we're so excited about the results we're >>Seeing. You know, one of the things that's kind of not core in the keynote theme, but I think it's underlying message is clear in the industry, is the developer productivity. You said making things easy is a big deal, self-service, getting in and trying, these are what developer friendly tools are like and platform. So I have to ask you, cuz this comes up a lot in our kind of business conversation, is, is if you take digital transformation concept to its completion, assuming now you know, as a thought exercise, you completely transform a company with technology that's, that is the business transformation outcome. Take it to completion. What does that look like? I mean, if you go there you'd say, okay, the company is the app, the company is the data, it's not a department serving the business, it's the business. And so I think this is kind of what we're seeing as the next big mountain climb, which is companies that do transform there, they are technology companies, they're not a department like it. So I think a lot of companies are kind of saying, wait a minute, why would we have a department? It should be the company. What's your your your view on this because this >>Yeah, so I I've had the for good fortune of being able to talk to thousand customers all over the world. And you know, one thing John, they never tell me, they never tell me that they're innovating too quickly. In fact, they always tell me the reverse. They tell me all the obstacles and impediments they have to be able to be able to be able to move fast. So one of the reasons they gravitate to MongoDB is just the speed that they wish they can build applications to, to your point, developer productivity. And by definition, developer productivity is a proxy for innovation. The faster you can make your developers, you know, move, the faster they can push out code, the faster they can iterate and build new solutions or add more capabilities on the existing applications, the faster you can innovate either to, again, seize new opportunities or to respond to new threats in your business. >>And so that resonates with every C level executive. And to your point, the developers not some side hustle that they kind of think about once in a while. It's core to the business. So developers have amassed enormous amount of power and influence. You know, their, their, their engineering teams are front and center in terms of how they think about building capabilities and and building their business. And that's also obviously enabled, you know, to your point, every software company, every company's not becoming a software company because it all starts with softwares, software enables, defines or creates almost every company's value proposition. >>You know, it makes me smile because I love operating systems as one of my hobbies in college was, you know, systems programming and I remember those network kind of like the operating systems, the cloud. So, you know, everything's got specialized capabilities and that's a big theme here at Reinvent. If you look at the announcements Monday night with Peter DeSantis, you got, you got new instances, new chips. So this whole engine kind of specialized component is like an engine. You got a core and you got other subsystems. This is gonna be an integral part of how companies architect their platform or you know, Adam calls it the landing zone or whatever they wanna call it. But you gotta start seeing a new architectural thinking for companies. What's your, can you share your experience on how companies should look at this opportunity as a plethora of more goodness on the hardware? On hardware, but like chips and instances? Cause now you can mix and match. You've got, you've got, you got everything you need to kind of not roll your own but like really build foundational high performance capabilities. >>Yeah, so I I, so I think this is where I think Amazon is really enabling all companies, including, you know, companies like Mon db, you know, push the envelope and innovation. So for example, you know, the, the next big hurdle for us, I think we've seen two big platform shifts over the last 15 years of platform shifts, you know, to mobile and the platform shift to cloud. I believe the next big platform shift is going from dumb apps to smart apps, which you're building in, you know, machine learning and you know, AI and just very sophisticated automation. And when you start automating human decision making, rather than, you know, looking at a dashboard and saying, okay, I see the data now, now I have to do this. You can automate that into your applications and make your applications leveraging real time data become that much more smart. And that ultimately then becomes a developer challenge. And so we feel really good about our position in taking advantage of those next big trends and software leveraging the price performance curves that, you know, Amazon continues to push in terms of their hardware performance, networking performance, you know, you know, price, performance and storage to build those next generation of modern applications. >>Okay, so let me get this straight. You have next generation intelligent smart apps and you have AI generative solutions coming out around the corner. This is like pretty good position for Mongo to be in with data. I mean, this is what you do, you're in that exactly of the action. What's it like? I mean, you must be like trying to shake the world and wake up. The world's starting to wake up now through this. So what's, what's it like? >>Well, I mean we're really excited and bullish about the future. We think that we're well positioned because we know as to your point, you know, we have amassed amazing amount of developer mindshare. We are the most popular modern data platform out there in the world. There's developers in almost every corner of the planet using us to do something. And to your point, leveraging data and these advances in machine learning ai. And we think the more AI becomes democratized, not, you know, done by a bunch of data scientists sitting in some corner office, but essentially enabling developers to have the tools to build these very, very sophisticated, smart applications will, you know, will position as well. So that's, you know, obviously gonna be a focus for us over the, frankly, I think this is gonna be like a 10 year, 10 15 year run and we're just getting started in this whole >>Area. I think you guys are really well positioned. I think that's a great point. And Adam mentioned to me and, and Mike interviewed, he said on stage talk about it, the role of a data analyst kind of goes away. Everyone's a data analyst, right? You'll still see specialization on, on core data engineering, which is kind of like an SRE role for data. So data ops and data as code is a big deal making data applications. So again, exciting times and you guys are well positioned. If you had to bumper sticker the event this week here at Reinvent, what would you, how would you categorize this this point in time? I mean, Adam's great leader, he is gonna help educate customers how to use technology to, for business advantage and transformation. You know, Andy did a great job making technology great and innovative and setting the table, Adam's gotta bring it to the enterprises and businesses. So it's gonna be an interesting point in time we're in now. What, how would you categorize this year's reinvent, >>Right? I think the, the, the tech world is pivoting towards what I'd call rationalization or cost optimization. I think people obviously in, you know, the last 10 years have, you know, it's all about speed, speed, speed. And I think people still value speed, but they wanna do it at some sort of predictable cost model. And I think you're gonna see a lot more focus around cost and cost optimization. That's where we think having one platform is by definition of vendor consolidation way for people to cut costs so that they can basically, you know, still move fast but don't have to incur the tax of using a whole bunch of different point tools. And so we think we're well positioned. So the bumper sticker I think about is essentially, you know, do more for less with MongoDB. >>Yeah. And the developers on the front lines. Great stuff. You guys are great partner, a top partner at AWS and great reflection on, on where you guys been, but really where you are now and great opportunity. David Didier, thank you so much for spending the time and it's been great following Mongo and the continued rise of, of developers of the on the front lines really driving the business and that, and they are, I know, driving the business, so, and I think they're gonna continue Smart apps, intelligent apps, ai, generative apps are coming. I mean this is real. >>Thanks John. It's great speaking with >>You. Yeah, thanks. Thanks so much. Okay.

(atmospheric music) >> Welcome to theCUBE Coverage of Data Citizens 2022 Collibra's Customer event. My name is Dave Vellante. With us is Kirk Haslbeck, who's the Vice President of Data Quality of Collibra. Kirk, good to see you, welcome. >> Thanks for having me, Dave. Excited to be here. >> You bet. Okay, we're going to discuss data quality, observability. It's a hot trend right now. You founded a data quality company, OwlDQ, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >> Yeah, absolutely. It's definitely exciting times for data quality which you're right, has been around for a long time. So why now? And why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before, and the variety has changed and the volume has grown. And while I think that remains true there are a couple other hidden factors at play that everyone's so interested in as to why this is becoming so important now. And I guess you could kind of break this down simply and think about if Dave you and I were going to build a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, what the ramifications could be, what those incidents would look like. Or maybe better yet, we try to build a new trading algorithm with a crossover strategy where the 50 day crosses the 10 day average. And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, kind of starts there, where everybody's realizing that we're all data companies, and if we are using bad data we're likely making incorrect business decisions. But I think there's kind of two other things at play. I bought a car not too long ago and my dad called and said, "How many cylinders does it have?" And I realized in that moment, I might have failed him cause I didn't know. And I used to ask those types of questions about any lock breaks and cylinders, and if it's manual or automatic. And I realized, I now just buy a car that I hope works. And it's so complicated with all the computer chips. I really don't know that much about it. And that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the individuals loading and consuming all of this data for the company actually may not know that much about the data itself and that's not even their job anymore. So, we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >> You know, the other thing too about data quality, and for years we did the MIT, CDO, IQ event. We didn't do it last year at COVID, messed everything up. But the observation I would make there, your thoughts is, data quality used to be information quality, used to be this back office function, and then it became sort of front office with financial services, and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well they sort of flipped the bit from sort of a data as a risk to data as an asset. And now as we say, we're going to talk about observability. And so it's really become front and center, just the whole quality issue because data's so fundamental, hasn't it? >> Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my favorite stock ticker app, and I check out the Nasdaq market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And that's kind of what's going on. There's so many numbers and they're coming from all of these different sources, and data providers, and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before Collibra. And what's been so exciting is, we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting, and why I think the CDO is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale, and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's not ever going to be based on one or two domain experts anymore. >> So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they cousins? What's your perspective on that? >> Yeah, it's super interesting. It's an emerging market. So the language is changing, a lot of the topic and areas changing. The way that I like to say it or break it down because the lingo is constantly moving, as a target on the space is really breaking records versus breaking trends. And I could write a condition when this thing happens it's wrong, and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. Everybody's talking about fresh data and stale data, and why would that matter? Well, if your data never arrived, or only part of it arrived, or didn't arrive on time, it's likely stale, and there will not be a condition that you could write that would show you all the good and the bads. That was kind of your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data. But it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there, there's more than a couple of these happening every day. >> So what's the Collibra angle on all this stuff? Made the acquisition, you got data quality, observability coming together. You guys have a lot of expertise in this area, but you hear providence of data. You just talked about stale data, the whole trend toward realtime. How is Collibra approaching the problem and what's unique about your approach? >> Well I think where we're fortunate is with our background. Myself and team, we sort of lived this problem for a long time in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with, before it was called data observability or reliability, was basically the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution. It's more advanced than some of the observation techniques that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights. And they want to see break records and breaking trends together, so they can correlate the root cause. And we hear that all the time. "I have so many things going wrong just show me the big picture. Help me find the thing that if I were to fix it today would make the most impact." So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows you can actually achieve total data governance. At this point with the acquisition of what was a Lineage company years ago, and then my company OwlDQ, now Collibra Data Quality. Collibra may be the best positioned for total data governance and intelligence in the space. >> Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was. They would just say, "Oh, it's a glitch." So they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you got to announce new products, right? It is your yearly event. What's new? Give us a sense as to what products are coming out but specifically around data quality and observability. >> Absolutely. There's this, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and BigQuery, and Databricks, Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook into these databases, and while we've always worked with the same databases in the past they're supported today. We're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now? Is everyone's concerned with something called Egress. Did my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? And with these native integrations that we're building and about to unveil here as kind of a sneak peak for next week at Data Citizens, we're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >> So this is interesting because what you just described, you mentioned Snowflake, you mentioned Google, oh actually you mentioned yeah, Databricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool. But then Google's got the open data cloud. If you heard, Google next. And now Databricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way, up until now I'm hearing, to really understand the relationships between all those and have confidence across, it's like yamarket AMI, you should just be a note on the mesh. I don't care if it's a data warehouse or a data lake, or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And that's what you're bringing to the table. Is that right? Did I get that right? >> Yeah, that's right. And it's, for us, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now we can send them the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network cost, zero egress cost, zero latency of time. And so when you were to log into BigQuery tomorrow using our tool, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage in access, privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there just like all of the major brands that you mentioned but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And we think that this positions us to be the leader there. >> I love this example because, we've got talks about well the cloud guys you're going to own the world. And of course now we're seeing that the ecosystem is finding so much white space to add value connect across cloud. Sometimes we call it super cloud and so, or inter clouding. Alright, Kirk, give us your final thoughts on the trends that we've talked about and data Citizens 22. >> Absolutely. Well I think, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there they want to know where everything is, where their sensitive data is, if it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're going to see more one click solutions, more SaaS based solutions, and solutions that hopefully prove faster time to value on all of these modern cloud platforms. >> Excellent. All right, Kirk Haslbeck, thanks so much for coming on theCUBE and previewing Data Citizens 22. Appreciate it. >> Thanks for having me, Dave. >> You're welcome. All right. And thank you for watching. Keep it right there for more coverage from theCUBE. (atmospheric music)

>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

>>Good afternoon everyone, and welcome back to the Cube. I am Savannah Peterson here, coming to you from Detroit, Michigan. We're at Cuban Day three. Such a series of exciting interviews. We've done over 30, but this conversation is gonna be extra special, don't you think, John? >>Yeah, this is gonna be a good one. Griffon Labs is here with us. We're getting the conversation of what's going on in the industry management, watching the Kubernetes clusters. This is large scale conversations this week. It's gonna be a good one. >>Yeah. Yeah. I'm very excited. He's also got a fantastic Twitter handle, twitchy. H Please welcome Richie Hartman, who is the director of community here at Griffon. Richie, thank you so much for joining us. Thanks >>For having me. >>How's the show been for you? >>Busy. I, I mean, I, I, >>In >>A word, I have a ton of talks at at like maintain a thing and like the covering board searches at the TLC panel. I run forme day. So it's, it's been busy. It, yeah. Monday, I didn't have to run anything. That was quite nice. But there >>You, you have your hands in a lot. I'm not even gonna cover it. Looking at your bio, there's, there's so many different things that you're working on. I know that Grafana specifically had some announcements this week. Yeah, >>Yeah, yeah. We had quite a few, like the, the two largest ones is a, we now have a field Kubernetes integration on Grafana Cloud. So our, our approach is generally extremely open source first. So we try to push stuff into the exporters, like into the open source exporters, into mixes into things which are out there as open source for anyone to use. But that's little bit like a tool set, not a ready made solution. So when we talk integrations, we actually talk about things where you get this like one click experience, You log into your Grafana cloud, you click, I have a Kubernetes, which probably most of us have, and things just work like you in just the data. You have to write dashboards, you have to write alerts, you have to write everything to just get started with extremely opinionated dashboards, SLOs, alerts, again, all those things made by experts, so anyone can use them. And you don't have to reinvent the view for every single user. So that's the one. The other is, >>It's a big deal. >>Oh yeah, it is. Yeah. It is. It, we, we has, its heavily in integrations course. While, I mean, I don't have to convince anyone that perme is a DD factor standard in everything. Cloudnative. But again, it's, it's, it's sometimes a little bit hard to handle or a little bit not easy to get into. So, so smoothing this, this, this path onto onboarding yourself onto this stack and onto those types of solutions. Yes. Is what a lot of people need. Course, if you, if you look at the statistics from coupon, and we just heard this in the governing board session yesterday. Yeah. Like 60% of the people here are first time attendees. So there's a lot of people who just come into this thing and who need, like, this is your path. This is where you should be going. Or at least if you want to go, go there. This is how to get there. >>Here's your runway for takeoff. Yes. Yeah. I think that's a really good point. And I love that you, you had those numbers. I was curious. I, I had seen on Twitter, speaking of Twitter, I had seen, I had seen that, that there were a lot of people here coming for the first time. You're a community guy. Are we at an inflection point where this community is about to continue to scale? >>That's a very good question. Which I can't really answer. So I mean, >>Obviously I bet you're gonna try. >>I covid changed a few things. Yeah. Probably most people, >>A couple things. I mean, you know, casually, it's like such a gentle way of putting that, that was >>Beautiful. I'm gonna say yes, just to explode. All these new ERs are gonna learn Prometheus. They're gonna roll in with a open, open metrics, open telemetry. I love it, >>You know, But, but at the same time, like Cuban is, is ramping back up. But if you look at the, if you look at the registration numbers between Valencia Andro, it was more or less the same. Interesting. Which, so it didn't go onto this, onto this flu trajectory, which it was on like, up to, up to 2019. I expect this to take up again. But also with the economic situation, everything, I, I don't think >>It's, I think the jury's still out on hybrid. I think there's a lot, lot more hybrid. Let's see how the projects are gonna go. That's what I think it's gonna be the tell sign. How many people are in participating? How are the project's advancing? Some of the momentum, >>I mean, from the project level, Most of this is online anyway. Of course. That's how open source, right. I've been working for >>Ages. That's >>Cause you don't have any trouble budget or, or any office or, It's >>Always been that way. >>Yeah, precisely. So the projects are arguably spearheading this, this development and the, the online numbers. I I, I have some numbers in my head, but I'm, I'm not a hundred percent certain to, but they're higher for this time in Detroit than in volunteer as far somewhere. Cool. So that is growing and it's grown in parallel, which also is great. Cause it's much more accessible, much more inclusive. You don't have to have a budget of at least, let's say, I don't know, two to five k to, to fly over the pond and, and attend this thing. You can just do it from your home. So that is, that's a lot more inclusive. And I expect this to, to basically be a second more or less orthogonal growth, growth path. But the best thing about coupon is the hallway track. I'm just meeting people, talking to people and that kind of thing is not really possible with, >>It's, it's great to see people >>In person. No, and it makes such a difference. I mean, yeah. Even and interviewing people in person too. I mean, it does a, it's, it's, and, and this, this whole, I mean cncf, this whole community, every company here is community first. It's how these projects come to be. I think it's awesome. I feel like you got something you're saying to say, Johnny. >>Yeah. And I love some of the advancements. Rich Richie, we talked last time about, you know, open telemetry, open metrics. You're involved in dashboards. Yeah. One of the themes here is ease of use, simplicity, developer productivity. Where do you see the ease of use going from a project standpoint? For me, as you mentions everywhere, it's pretty much, it is, it's almost all corners of the world. Yep. And new people coming in. How, how are you making it easier? What's going on? Give us the update on that. >>So we also, funnily enough at precisely this topic in the TC panel just a few hours ago, about ease of use and about how to, how to make things easier to, to handle how developers currently, like if they just want to get into the cloud native seen, they have like, like we, we did some neck and math, like maybe 10 tools at least, which you have to be somewhat proficient in to just get started, which is honestly horrendous. Yeah. Course. Like with a server, I just had my survey install my thing and it runs, maybe I need a database, but that's roughly it. And this needs to change again. Like it's, it's nice that everything is, is un unraveled. And you have, you, you, you, you don't have those service boundaries which you had before. You can do all the horizontal scaling, you can do all the automatic scaling, all those things that they're super nice. But at the same time, this complexity, which used to be nicely compartmentalized, was deliberately broken up. And so it's becoming a lot harder to, to, like, we, we need to find new ways to compartmentalize this complexity back to, to human understandable levels again, in particular, as we keep onboarding new and new and new, new people, of course it's just not good use of anyone's time to, to just like learn the basics again and again and again. This is something which should be just compartmentalized and automated away. We're >>The three, We were talking to Matt Klein earlier and he was talking about as projects become mature and all over the place and have reach and and usage, you gotta work on the boring stuff. Yes. And when it's boring, that means you have success. Yes. But then you gotta work on the plumbing. What are some of the things that you guys are working on? Because people are relying on the product. >>Oh yeah. So for with my premises head on, the highlight feature is exponential or native or spars. Histograms. There's like three different names for one single concept. If you know Prometheus, you ha you currently have hard bucket boundaries where I say my latency is lower equal two seconds, one second, a hundred milliseconds, what have you. And I can put stuff into those histogram buckets accordingly to those predefined levels, which is extremely efficient, but like on the, on the code level. But it's not very nice for the humans course you need to understand your system before you're able to, to, to choose good cutoff points. And if you, if you, if you add new ones, that's completely fine. But if you want to actually change them, course you, you figured out that you made a fundamental mistake, you're going to have a break in the continue continuity of your observability data. And you cannot undo this in, into the past. So this is just gone native histograms. On the other hand, allow me to, to, okay, I'm not going to get get into the math, but basically you define a single formula, which there comes a good default. If you have good reasons, then you can change it. But if you don't, just don't talk, >>The people are in the math, Hit him up on Twitter. Twitter, h you'll get you that math. >>So the, >>The thing is people want the math, believe me. >>Oh >>Yeah. I mean we don't have time, but hit him up. Yeah. >>There's ProCon in two weeks in Munich and there will be whole talk about like the, the dirty details of all of the stuff. But the, the high level answer is it just does what people would expect it to do. And with very little overhead, you become, you get highly, highly or high resolution histograms, which is really important for a lot of use cases. But this is not just Prometheus with my open metrics head on the 2.0 feature, like the breaking highlight feature of Open Metrics 2.0 will be you guested precisely the same with my open telemetry head on. Low and behold the same underlying technology is being put or has been put into open telemetry. And we've worked for month and month and month and even longer between all different projects to, to assert that we have one single standard which is actually compatible with each other course. One of the worst things which you can have in the cloud ecosystem is if you have soly different things and they break in subtly wrong ways, like it's much better to just not work than to break in a way, which is just a little bit wrong. Of course you won't figure this out until it's too late. So we spent, like with all three hats, we spent insane amounts of time on making this happen and, and making this nice. >>Savannah, one of the things we have so much going on at Cube Con. I mean just you're unpacking like probably another day of cube. We can't go four days, but open time. >>I know, I know. I'm the same >>Open telemetry >>Challenge acceptance open. >>Sorry, we're gonna stay here. All the, They >>Shut the lights off on us last night. >>They literally gonna pull the plug on us. Yeah, yeah, yeah, yeah. They've done that before. It's not the first time we go until they kick us out. We love, love doing this. But Open telemetry is got a lot of news too. So that's, We haven't really talked much about that. >>We haven't at >>All. So there's a lot of stuff going on that, I won't call it boring. That's like code word's. That's cube talk for, for it's working. Yeah. So it's not bad, but there's a lot of stuff going on. Like open telemetry, open metrics, This is the stuff that matters cuz when you go in large scale, that's key. It's just what, missing all the, all the stuff. >>No, >>What are we missing? What are people missing? What's going on in the show that you think that's not actually being reported on? I mean it's a lot of high web assembly for instance got a lot >>Of high. Oh yeah, I was gonna say, I'm glad you're asking this because you, you've already mentioned about seven different hats that you wear. I can only imagine how many hats are actually in your hat cabinet. But you, you are someone with your, with your fingers in a lot of different things. So you can kind of give us a state of the union. Yeah. So go ahead. Let's talk about >>It. So I think you already hit a few good points. Ease of use is definitely one of them. And, and improving the developer experience and not having this like a value of pain. Yeah. That is one of the really big ones. It's going to be interesting cause it is boring. It is janitorial and it needs a different type of persona. A lot of, or maybe not most, but a large fraction of developers like the shiny stuff. And we could see this in Prometheus where like initially the people who contributed this the most where like those restless people who need to fix that one thing, this is impossible, are going to do it. Which changed over the years where the people who now contribute the most are off the janitorial. Like keep things boring, keep things running, still have substantial changes. But but not like more on the maintenance level. >>Yeah. The maintainers. I was just gonna bring that >>Up. Yeah. On the, on the keep things boring while still pushing 'em forward. Yeah. And the thing about ease of use is a lot of this is boring. A lot of this is strategy. A lot of this is toil. A lot of this takes lots of research also in areas where developers are not really good at, like UX for example, and ui like most software developers are really bad at those cause they just think differently from normal humans, I guess. >>So that's an interesting observation that you just made. I we could unpack that on a whole nother show as well. >>So the, the thing is this is going to be interesting for the open source scene course. This needs deliberate investment by companies who assign people to those projects and say, okay, fix that one thing or make it easier to use what have you. That is a lot easier with, with first party products and projects from companies cuz they can invest directly into the thing and they see much more of a value prop. It's, it's kind of normal by now to, to allow developers or even assigned developers onto open source projects. That's not so much the case for the tpms, for the architects, for the UX and your I people like for the documentation people that there's not as much awareness of that this is also driving value for everyone. Yes. And also there's not much as much. >>Yeah, that's a great point. This whole workflow production system of open source, which has grown and keeps growing and we'll keep growing. These be funded. And one of the things we were talking earlier in another session about is about the recession potentially we're hitting and the global issues, macroeconomics that might force some of these projects or companies not to get VC >>Funding. It's such a theme at the show. So, >>So to me, I said it's just not about VC funding. There's other funding mechanisms that's community oriented. There's companies participating, there's other meccas. Richie, if you could have your wishlist of how things could progress an open source, what would you want to see happen in terms of how it's, how things are funded, how things are executed. Cuz developers are going to run businesses. Cuz ultimately if you follow digital transformation to completion, it and developers aren't a department serving the business. They are the business. And that's coming fast. You know, what has to happen in your opinion, if you had the wish magic wand, what would you, what would you snap your fingers to make happen? >>If I had a magic wand that's very different from, from what is achievable. But let, let's >>Go with, Okay, go with the magic wand first. Cause we'll, we'll, we'll we'll riff on that. So >>I'm here for dreams. Yeah, yeah, >>Yeah. I mean I, I've been in open source for more than two, two decades, but now, and most of the open source is being driven forward by people who are not being paid for those. So for example, Gana is the first time I'm actually paid by a company to do my com community work. It's always been on the side. Of course I believe in it and I like doing it. I'm also not bad at it. And so I just kept doing it. But it was like at night on the weekends and everything. And to be honest, it's still at night and in the weekends, but the majority of it is during paid company time, which is awesome. Yeah. Most of the people who have driven this space forward are not in this position. They're doing it at night, they're doing it on the weekends. They're doing it out of dedication to a cause. Yeah. >>The commitment is insane. >>Yeah. At the same time you have companies mostly hyperscalers and either they have really big cloud offerings or they have really big advertisement business or both. And they're extracting a huge amount of value, which has been created in large part elsewhere. Like yes, they employ a ton of developers, but a lot of the technologies they built on and the shoulders of the giants they stand upon it are really poorly paid. And there are some efforts to like, I think the core foundation like which redistribute a little bit of money and such. But if I had my magic wand, everyone who is an open source and actually drives things forwards, get, I don't know, 20% of the value which they create just magically somehow. Yeah. >>Or, or other companies don't extract as much value and, and redistribute more like put more full-time engineers onto projects or whichever, like that would be the ideal state where the people who actually make the thing out of dedication are not more or less left on the sideline. Of course they're too dedicated to just say, Okay, I'm, I'm not doing this anymore. You figure this stuff out and let things tremble and falter. So I mean, it's like with nurses and such who, who just like, they, they know they have something which is important and they keep doing it. Of course they believe in it. >>I think this, I think this is an opportunity to start messaging this narrative because yeah, absolutely. Now we're at an inflection point where there's a big community, there is a shared responsibility in my opinion, to not spread the wealth, but make sure that it's equally balanced and, and the, and I think there's a way to do that. I don't know how yet, but I see that more than ever, it's not just come in, raid the kingdom, steal all the jewels, monetize it, and throw some token token money around. >>Well, in the burnout. Yeah, I mean I, the other thing that I'm thinking about too is it's, you know, it's, it's the, it's the financial aspect of this. It's the cognitive load. And I'm curious actually, when I ask you this question, how do you avoid burnout? You do a million different things and we're, you know, I'm sure the open source community that passion the >>Coach. Yeah. So it's just write code, >>It's, oh, my, my, my software engineering days are firmly over. I'm, I'm, I'm like, I'm the cat herer and the janitor and like this type of thing. I, I don't really write code anymore. >>It's how do you avoid burnout? >>So a i I didn't curse ahead burnout a few years ago. I was not nice, but that was still when I had like a full day job and that day job was super intense and on top I did all the things. Part of being honest, a lot of the people who do this are really dedicated and are really bad at setting boundaries between work >>And process. That's why I bring it up. Yeah. Literally why I bring it up. Yeah. >>I I I'm firmly in that area and I'm, I'm, I don't claim I have this fully figured out yet. It's also even more risky to some extent per like, it's, it's good if you're paid for this and you can do it during your work time. But on the other hand, if it's so nice and like if your hobby and your job are almost completely intersectional, it >>Becomes really, the lines are blurry. >>Yeah. And then yeah, like have work from home. You, you don't even commute anything or anymore. You just sit down at your computer and you just have fun doing your stuff and all of a sudden it's deep at night and you're still like, I want to keep going. >>Sounds like God, something cute. I >>Know. I was gonna say, I was like, passion is something we all have in common here on this. >>That's the key. That is the key point There is a, the, the passion project becomes the job. But now the contribution is interesting because now yeah, this ecosystem is, is has a commercial aspect. Again, this is the, this is the balance between commercialization and keeping that organic production system that's called open source. I mean, it's so fascinating and this is amazing. I want to continue that conversation. It's >>Awesome. Yeah. Yeah. This is, this is great. Richard, this entire conversation has been excellent. Thank you so much for joining us. How can people find you? I mean, I give em your Twitter handle, but if they wanna find out more about Grafana Prometheus and the 1700 things you do >>For grafana grafana.com, for Prometheus, promeus.io for my own stuff, GitHub slash richie age slash talks. Of course I track all my talks in there and like, I don't, I currently don't have a personal website cause I stop bothering, but my, like that repository is, is very, you find what I do over, like for example, the recording link will be uploaded to this GitHub. >>Yeah. Great. Follow. You also run a lot of events and a lot of community activity. Congratulations for you. Also, I talked about this last time, the largest IRC network on earth. You ran, built a data center from scratch. What happened? You done >>That? >>Haven't done a, he even built a cloud hyperscale compete with Amazon. That's the next one. Why don't you put that on the >>Plate? We'll be sure to feature whatever Richie does next year on the cube. >>I'm game. Yeah. >>Fantastic. On that note, Richie, again, thank you so much for being here, John, always a pleasure. Thank you. And thank you for tuning in to us here live from Detroit, Michigan on the cube. My name is Savannah Peterson and here's to hoping that you find balance in your life this weekend.

(bright upbeat music) >> Welcome to theCUBE's Coverage of Data Citizens 2022 Collibra's Customer event. My name is Dave Vellante. With us is Kirk Hasselbeck, who's the Vice President of Data Quality of Collibra. Kirk, good to see you. Welcome. >> Thanks for having me, Dave. Excited to be here. >> You bet. Okay, we're going to discuss data quality, observability. It's a hot trend right now. You founded a data quality company, OwlDQ and it was acquired by Collibra last year. Congratulations! And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >> Yeah, absolutely. It's definitely exciting times for data quality which you're right, has been around for a long time. So why now, and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as to why this is becoming so important now. And I guess you could kind of break this down simply and think about if Dave, you and I were going to build, you know a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, what the ramifications could be? What those incidents would look like? Or maybe better yet, we try to build a new trading algorithm with a crossover strategy where the 50 day crosses the 10 day average. And imagine if the data underlying the inputs to that is incorrect. We'll probably have major financial ramifications in that sense. So, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. I bought a car not too long ago and my dad called and said, "How many cylinders does it have?" And I realized in that moment, I might have failed him because 'cause I didn't know. And I used to ask those types of questions about any lock brakes and cylinders and if it's manual or automatic and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips. I really don't know that much about it. And that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the individuals loading and consuming all of this data for the company actually may not know that much about the data itself and that's not even their job anymore. So, we'll talk more about that in a minute but that's really what's setting the foreground for this observability play and why everybody's so interested, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >> You know, the other thing too about data quality and for years we did the MIT CDOIQ event we didn't do it last year at COVID, messed everything up. But the observation I would make there love thoughts is it data quality used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a a risk to data as an asset. And now, as we say, we're going to talk about observability. And so it's really become front and center, just the whole quality issue because data's fundamental, hasn't it? >> Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And that's kind of what's going on. There's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor. But with the scale that we've achieved in early days, even before Collibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is listening right intently nowadays to this topic is so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's not ever going to be based on one or two domain experts anymore. >> So, how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they cousins? What's your perspective on that? >> Yeah, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the lingo is constantly moving as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens it's wrong and when it doesn't, it's correct. Or I could look for a trend and I'll give you a good example. Everybody's talking about fresh data and stale data and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good and the bads. That was kind of your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >> So what's the Collibra angle on all this stuff made the acquisition you got data quality observability coming together, you guys have a lot of expertise in this area but you hear providence of data you just talked about stale data, the whole trend toward real time. How is Collibra approaching the problem and what's unique about your approach? >> Well, I think where we're fortunate is with our background, myself and team we sort of lived this problem for a long time in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution. It's more advanced than some of the observation techniques that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong just show me the big picture. Help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact connecting it with lineage and catalog, metadata. And as that grows, you can actually achieve total data governance. At this point, with the acquisition of what was a lineage company years ago and then my company OwlDQ, now Collibra Data Quality, Collibra may be the best positioned for total data governance and intelligence in the space. >> Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, they just said, "Oh, it's a glitch." So they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens '22 that you're announcing you got to announce new products, right? Your yearly event, what's new? Give us a sense as to what products are coming out but specifically around data quality and observability. >> Absolutely. There's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks, Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a salike model. And we've started to hook in to these databases. And while we've always worked with the same databases in the past they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did my data that I've spent all this time and money with my security team securing ever leave my hands? Did it ever leave my secure VPC as they call it? And with these native integrations that we're building and about to unveil here as kind of a sneak peek for next week at Data Citizens, we're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration you could log into the Collibra Data Quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >> So this is interesting because what you just described you mentioned Snowflake, you mentioned Google, oh actually you mentioned yeah, the Data Bricks. Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool but then Google's got the open data cloud. If you heard Google Nest and now Data Bricks doesn't call it the data cloud but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm hearing to really understand the relationships between all those and have confidence across, it's like (indistinct) you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And that's what you're bringing to the table. Is that right? Did I get that right? >> Yeah, that's right. And for us, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now we can send them the operating ability to crunch all of the calculations, the governance, the quality and get the answers. And what that's doing, it's basically zero network cost, zero egress cost, zero latency of time. And so when you were to log into Big BigQuery tomorrow using our tool or let or say Snowflake, for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls things of that nature that just become less onerous. What we're seeing is there's so much technology out there just like all of the major brands that you mentioned but how do we make it easier? The future is about less clicks, faster time to value faster scale, and eventually lower cost. And we think that this positions us to be the leader there. >> I love this example because every talks about wow the cloud guys are going to own the world and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. Alright, Kirk, give us your final thoughts and on the trends that we've talked about and Data Citizens '22. >> Absolutely. Well I think, one big trend is discovery and classification. Seeing that across the board people used to know it was a zip code and nowadays with the amount of data that's out there, they want to know where everything is where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases, how fast they can get controls and insights out of their tools. So I think we're going to see more one click solutions, more SAS-based solutions and solutions that hopefully prove faster time to value on all of these modern cloud platforms. >> Excellent, all right. Kurt Hasselbeck, thanks so much for coming on theCUBE and previewing Data Citizens '22. Appreciate it. >> Thanks for having me, Dave. >> You're welcome. All right, and thank you for watching. Keep it right there for more coverage from theCUBE.

(melodic music) >> Good afternoon. Welcome back to Chicago. Lisa Martin here with John Furrier. Day one of our coverage of Ansible Fest 2022. John, it's great to be back in person. People are excited to be here. >> Yeah. We've had some great conversations with folks from Ansible and the community and the partner side. >> Yeah. One of the things I always love talking about John, is talking with organizations that have been around for a long time that maybe history, maybe around nearly a hundred years, how are they embracing technology to modernize? Yeah, we got a great segment here with the financial services leader, end user of Ansible. So it's be great segment. >> Absolutely. Please welcome Noor Shadid to the program, the senior SVP, excuse me, senior technology manager at Wells Fargo. Noor it's great to have you on theCUBE. Thank you for joining us. >> Of course. Happy to be here. >> Thanks. >> Talk a little bit about technology at Wells Fargo. I was mentioning to you I've been a longtime customer and I've seen the bank evolve incredibly so in the years I've been with it. But... >> Yeah. >> ...talk about Wells Fargo was a technology-driven company. >> Yeah. So I like to consider Wells, right? Being in a financial institution company. So I consider us a technology company that does banking as a customer, right? Like we were talking about. There's so much that we've been able to release over the couple of years, right? I mean, decades worth of automation and technology has been coming out, but lately, right? The way we provide for our customers, how fast at scale, what we're doing for our customers, it's been, it's been significant, right? And I think our goal is always how can we enhance the process for our customers and how can we provide them the next best thing? And I think technology has really allowed us to evolve with our customers. >> The customers. We are so demanding these days. Right? I think one of the things that short supplied in the last two years was patience and tolerance. >> Yes. >> People. And I don't think that's going to rubber band back? >> Yeah. No, I don't think so. >> So how, talk to us about how Wells is using automation to really drive innovation and, surprise and delight those customers on a minute by minute basis. >> Yeah. And so, you know, if you think about banking, we've been able, with automation, we've been able to bring banking into the 21st century. You do not have to go to a branch to manage your money anymore. You do not have to go, you know, go to deposit your check inside of a branch. You can do it through your mobile app, right? That's driven by automation and innovation, right? And, you know, we have all of these back ends tools working for us to help get us to this next generation of, of banking. We can instantly send money to each other. We don't have to worry about, I need to go and figure out how I'm going to get money to this person and I need to wait, you know, X amount of days. You, you have the ability and you have, you feel safe being able to manage your money at the organization. And so automation has really allowed us to get to this place where we can constantly enhance and provide features and reliability to our customers. >> It's interesting you mentioned that you guys are a technology can have it do banking reminds me of the old iPhone analogy. It's a computer that happens to make phone calls. >> Yeah. >> So like, this is the similar mindset. How do you guys keep up? >> Yeah. >> With the technology? >> So it's tough, right? Because there's so much that comes out. And I think the only thing that's constant in technology is change, right? Because it's constantly evolving. But what we do is we, integrate very well with these new tools. We do proof of concepts where we try to, you know, what's on the market, what's hot, how can we involve, like, how can we involve these new tools in our processes? How can we provide a better end result for our customers by bringing in these new tools? So we have a lot of different teams that bring, you know, their jobs are to like, do these proof of concepts and help us build and evolve our own strategies, right? So it keeps us, it keeps us on our toes and I think it keeps, you know, all these new things that are coming out in the market. We're a part of it. We want to evolve with those, what the latest and greatest is. And it's, it's been working right as customers of financial services and us managing our money through, you know, through banks. It's been great. >> So the business is the application. >> Yes. >> And how do you guys make that happen when it comes down to getting the teams aligned? What's the culture like? Explain. >> Yeah. So at Wells we have evolved so much over the, over the last few years. The culture right now is we want to make changes. You know, we are making changes. We want to drive through innovation. We want to be able to provide our, you know, it's a developer centric approach right now, right? We want to push to the next and the greatest. And so everybody is excited and everybody's adapting to all of what's happening in the environment right now. So it's been great because we are able to use all of these new features and tools and things that we were just talking about by allowing our developers to do that work and allowing people to learn these new skills and be able to apply them in their jobs, which is now creating this, you know, a better result for our customers because we're releasing at such a faster pace. And at scale. >> Talk about how, you talked about multiple groups in the organization really investing in innovative technology. How do you get buy-in? What's that sort of pyramid like up to the top level? >> Yeah. >> Because to your point, you're making changes very quickly and consumers demand it. >> Yep. >> You can do everything from home these days. >> Yep. >> You don't have to go into a branch. >> Yeah, yeah. >> Which has changed dramatically in the last it's. >> Powerful few years. Yeah. >> But how, what's that buy-in conversation like from our leadership? >> Yeah. If you don't have leadership buy-in, it's very difficult to make those changes happen. But we at Wells have such a strong support from our leadership to be a part of the change and be, you know, constantly evolve and get better. So the way we work, cause we're such a large organization, you know, we bring in our business, you know, our business teams and we talk to them about what is it that's best going to better our customers. How do we also not just support external but internal, right? How do we provide these automated tools or processes for people to want to do this next work and, and do these, you know, these new releases for our customers. And so we bring in our business partners and, and we bring in our leadership and, our stakeholders and we kind of present to them, you know, this is what we're trying to do. This is the return that you'll get. This is what our customers will also receive. And this is, you know, this is how we keep evolving with that. >> How has the automation culture changed? Because big discussion here is reuse, teamwork, I call it multiplayer kind of organizations where people are working together. 'Cause that's a big theme of automation. >> Yeah. >> Reuse, leverage. >> Yep. >> Can you explain how you guys look at that? >> Yeah. It's changed the way that we do banking because we're eliminating a lot of the repetitive tasks in the toil because we have partners that are developing these, you know, services. So specifically with Ansible, we have these playbooks, rather than having every customer write the same playbook but with their own little, you know, flavor to it, we're able to create these generic patterns that customers can just consume simply by just going into a tool, filling out you know, filling out that playbook template, credentials, or whatever it is that they need and executing it. They don't have to worry about developing something from scratch. And it also allows our customers to feel safe because they don't have to have those skills out the box to be able to use these automation tools, right? They can use what's already been written and executed. >> So that make things go faster with the benefits or what? Speed? >> Faster stability, right? We're now speed, stability, scalability, because we're now able to use this at scale. It's not just individual teams trying to do this within small spaces. We're able to reliable, right? Automation allows us to be reliable internally and for our customers. Because you're not asking, there's no human intervention when you're automating, right? You have these opportunities now for people to just, it's one click, you know, one click solution or you're, you're end to end. You got self-healing involved. It's really driving the way that we do our work today. >> So automation sounds like it's really fueling the internal employee experience at Wells... >> Yes. >> ...as well as the customer experience. And those two things are like this to me. They're inextricably linked. >> A hundred percent because if you need it, they need to be together, right? You want your internal to also be happy because they want to be able to develop these solutions and provide these automation opportunities for our teams, right? And so with the customers, they're constantly seeing these great features come out, right? We can, you know, with AIML today, we're now able to detect fraud significantly. What we would've, what we could've done a couple years ago. And, and developers are excited to be able to do that, right? To be able to learn all these new tools and new technologies. >> What's interesting Wells is you guys are like an edge application. Obviously everyone's got banking in their hand. FinTech obviously money's involved. So there's people interested in getting that money. >> Yeah. >> Security hackers or whatnot. So when you got speed and you got the consistency, I get that. As you look at securing the app, that becomes a big part of what, what's the conversations like there? >> Yeah. >> 'Cause that's the number one concern. And it's an Edge app. I got my mobile, I got my desktop. >> Yeah. >> Everything's in the cloud on premise. >> Yeah. And, and I think for us, security is number one. You know, we want to make sure that we are providing the best for our customers and that they feel safe. Banking, whatever financial service you're working with, you want to feel like you can trust that your money with those services. Right? So what we do is we make sure that our security partners are with us from day one. They're a part of the process. They're automating their pieces as well. We don't want to rely on humans to do a lot of the manual work and do the checking and the logging. You want it to be through automation and new tools, right? You want it to be done through trusted services. You don't, you know, security is right there with us. They're part of our technology organization. They are in the technology org. So they're the ones that are helping us get to that next generation to provide, you know, more secure processes and services for customers. >> And that's key for trust. >> Yes. >> And trust is critical to reduce churn and to, you know, increase the customer lifetime value. But, but people, I mean, especially with the amount of generations that are alive today in banking, you need to be able to deliver that trust intrinsically to any customer. >> Yes, a hundred percent. And you want to be able to not only trust the service but yourself that you can do it. You know, when you go into your app and you make a payment, or when you go in and you want to send, you know, you want to send money to a different, you know, a different bank account, you want to be able to know that what you just did is secure and is where you plan to send it. And so being able to create that environment and provide those services is, is everything right for our customers. >> What are some of the state-of-the-art kind of techniques or trade craft around building apps? 'Cause I mean, basically you're digitally transformed. I mean, you guys are technology first. >> Yeah. >> The app is the company. >> Yeah. >> That's, that's the bank. How do you stay current? What's some of the state of the art things that you guys do that wasn't around just a few years ago? >> Yeah, I mean, right now just using, we're using tools like Terraform and Ansible. We're making sure that those two are hand in hand working well together. So when we work on provisioning, when we, during provisioning where it's all, you know, it's automated, fully end to end, you know, AI ops, right? Being able to detect reoccurring issues that are happening. So if you have a incident we want to learn from that incident and we want to be able to create, you know, incident tickets without having to rely on a human to find that, you know, that problem that was occurring and self-healing, right? All of this is starting to evolve and bringing in the, the proper alerting tools, bringing in the pro, you know, the right automation tools to allow that self-healing to work. That's, you know, these are things that we didn't have, you know, year, decade ago. This is all coming out now as we're starting to progress and, and really take innovation and, you know, automation itself.... >> What's the North star internally when you guys say, hey, you know, down five years down the road, bridge to the future, we're transforming, we've continued to innovate. Scale is a big deal. Data, data sovereignty, all these things are coming up. And what's the internal conversation like when you talk about a future state? >> Yeah, I think right now we're on our cloud transformation journey, right? We're moving right now. We have workloads into our two CSPs or public cloud. Also providing a better service for infrastructure and being able to provide services internally at a faster space, right? So moving into the public cloud, making sure everything's virtualized, moving away from hard, you know, physical hardware or physical servers. That's kind of the journey that we're on right now. Right? Also, machine learning. We want to be able to rely on these, you know, bots. We want to be able to rely on, on things learning from what we're doing so that we don't make the same mistakes again. >> Where would you say the most value or the highest ROI that you've gotten from automation today? Where is that in the organization? >> There's so much, but what I mean because of all of the work that we're doing, there's a lot that I could list, but what I will say is that the ability to allow self-healing in our environments without causing issues is a very big return. Automating failovers, right? I think a lot of our financial institutions have made that a priority where they want to make sure that their applications are active, active and also that when things do go wrong, there is something in place to make sure that that incident actually doesn't, you know, take down any problems. I think it's just also investing in people. Right now, the market is hot and we want to make sure that people feel like they're being able to contribute, they're using the latest and greatest tools. They're able to upskill within our own environments at the firm. And I think our organization does an amazing job of prioritizing people. And so we see the return because we're prioritizing people. And I think, you know, a lot of institutions are trying, you know, people first, people first. But I can say that at Wells, because we are actually driving this, we're allowing, you know, we're enforcing that. We want our engineers to get the certifications. We're providing, you know, vouchers so that people can get those clouds certifications. It's when you do that and you put people first, everything kind of comes together. And I think, you know, a lot of what we see in our industry, it's not really the technology that's the problem, it's process because you're so, you know, we're working at large scales. Our environments are massive. So, you know, my three years at Wells have seen a significant amount of change that has really driven us to be.... >> On that point better. How about changing of the roles? IT, I mean, back in the day, IT serves the business, you know, IT is the business now, right? As, as you've been pointing out. What does the roles change of as automation scales in, is it the operator? I mean, we know what's going on with dev's devs are doing more IT in the CICD pipe lining. >> Yep. >> So we see that velocity check, good cloud native development. What's the op scene look like? It seems to be a multi-tool role. >> Yeah. >> Where the versatility of the skill set... >> Yep. >> ...is the quick learner. >> Yep, able to adapt. >> And yeah, what's your view on this new persona that's emerging from this new opportunity? >> Yeah, and I think it's a great question because if you think about where we're going, and even the term DevOps, right? It means so many things to different people. But literally when you think about what DevOps is allowing our developers and our operations to work together on one team, it's allowing, you know, our operation engineers aren't, you know, years ago, ops engineers were not doing the development work. They were relying on somebody to do the development work and they were just supporting making sure our systems were always available, right? Our engineers are ops are now doing the development work. They're able to contribute and to get, they're writing their own playbooks. They're able to take them into production and ensure that they're, being used correctly. We are change driven execution organization. Everything is driven through change and allowing our ops engineers or production score engineers to write their own playbooks, right? And they know what's happening in the environment. It's powerful. >> Yeah. You're seeing DevOps become a job title. >> Yeah (laughs). >> Used to be like a function of philosophy... >> Yeah, yeah. >> ... and then SRE's... >> SRE's. >> SRE are like how many servers do you have? I don't know, a cloud, what's next? (all laugh) >> What's next? Yeah, I think with SREs it's, you know, it's important that if you have site reliability engineers, you're working towards, you know, those non-functional requirements... >> Yeah. >> ...making sure that you're handling those key components that are required to ensure that our systems, our applications and our integrations, you know, are up there and they're meeting the standards that we set for those other faults. >> And, and I think Red Hat Ansible nailed it here because infrastructure is code. We get that infrastructure has configuration as code, but OPS says code really is that SRE outcome. SRE also came from the Google background, but that means infrastructure's just doing, it's thing. >> Yes. >> The ops is automated. >> Yes. >> That's an interesting concept. >> Yeah, because it's not, you know, it's still new, right? A lot of organizations used to see, and they probably still see operations as being the, you know, their role is just to make sure that the lights are on and they have specific access so they, you know, they're not touching code, but the people that are doing the work and know the environment should really be the ones under creating the content for it. So yeah, I mean it's crazy what's happening now. >> So I got an analogy that's going to be banking analogy, but for tech, you know, back in the automation, Oh, going to put my job out of business, ATMs are going to put the teller out of business as more tellers now than there are before the ATMs. So that metaphor applies into tech where people are like, "What am I auto? What's automating away? Is it my job?" And so actually people know it's not. >> Yeah. >> But what does that free up? So if you assume, if you believe that's good, you say, okay, all the grunt work and the low level on differentiated heavy lifting gets automated away. >> Yeah. >> Great. What does that free up the talent to do? >> Yeah, so when you, and that's great that you bring it up because I think people fear, you know, of automation, especially people that weren't doing automation in the past and now their roles are now they're able to automate those roles out. They're fearful that they don't have a space, a role anymore. But that's not the case at all. What we prioritize is now that those new engineers have this new skill set, apply them. Start using it to be a part of this transformation, right? We're moving from, we went from physical to virtual to now, you know, we're moving into the public, moving into the cloud, right? And that, that transformation, you need people who are ramping up their skill sets, you know, being a part of one of the tools that I own is terraform at Wells that, you know, right now our priority is we're trying to ramp up the organization to learn terraform, right? We want people to learn, you know, this new syntax, this new, you know, HCL and it's, you know, people have been automating some of the stuff that they're doing in their day to day and now trying to learn something new so that they can contribute to this new transformation. >> So new functionality, higher value services? >> Yes, yeah. >> It brings tremendous opportunity for those folks involved in automation. >> Yes. >> or on so many levels. >> Yep. >> Last question, Noor for you is what, you know, as we are rounding out calendar year 2022, entering into 2023, that patience is, that we talked about is still not coming back. What's next for Wells as a technology company that does banking? >> I mean, you name it, we're working on it, because we want to be able to deliver the best for our customers. And I think right now, you know, our digital transformation strategy and, and moving into the public cloud and getting our applications re-architected so that we are moving into microservice driven apps, right? We're moving these workloads into the public cloud in a seamless way. We're not lifting and shifting so that we're not causing more problems into the environment. Right. And I think our, our, our goal is right, Like I was saying earlier, people and evolving with the technology that's coming out. We're not, you know, we are a part of the change and we are happy to be a part of that change and making those changes happen. >> People first. >> Awesome, awesome stuff. >> Automation first sounds outstanding and I will never look at Wells Fargo as a bank again. >> Yeah. (laughter) >> Perfect. Perfect. >> Yeah, that's awesome. >> It's been such a pleasure having you on the program, talking about how transformative Wells has been and continues to be. >> Yeah. >> We appreciate your insights and your time. >> Thank you. >> Thank you so much. It was lovely being her. Pleasure here. Thank you guys. >> For our guest and John Furrier, I'm Lisa Martin. You've been watching theCUBE all day, I'm sure, live from Chicago at Ansible Fest 2022. We hope you have a wonderful rest of your day and John and I will see you tomorrow morning.

(soft music) >> Hey, welcome back to theCUBE's coverage from Miami of IFS Unleashed 2022, Lisa Martin here with you. We've had great conversations today with IFS execs, customers, partners. Our ecosystem is quite robust and quite strong. And we've had some alumni on, I've got another alumni who's back with me, Michael Ouissi, the group's COO of IFS. Michael, welcome back to theCUBE. >> Thanks for having us, my pleasure. >> It's great to be back in-person. >> Absolutely. >> It was great to walk into the keynote this morning and see a full room. I was talking with Darren Roos, your CEO earlier this morning and I said, it must have felt great to walk out on stage and actually see a sea of people and customers and partners who want to engage and get that relationship with IFS just turbocharged. >> Absolutely, I mean, it's been three years, we haven't had this buzz, this energy, and the opportunity to actually see all our customers and also show our customers who we are, how we are evolving and how we're becoming a different company over the past four years. >> And it's impressive what IFS has done in that timeframe. All the conversations I've had today, really reflect the strategy, the strong strategy and vision that this company has. But I was looking at some of the financials and saw that your first half of 2022, which ended in June, there was tremendous growth. ARR up 33%, I think they're recurring revenue is in the 70 percentile now. Lot of new customers, a lot of of trust that existing customers are showing to the company. >> Yeah, absolutely. Look, and I think the secret sauce is that we have focused on where our strengths are, we haven't gone astray, we haven't tried to actually capture growth in any other vertical. We are really very religious about where we're going and there, where we are going, we are going deep and we really are trying to be the best version of ourselves for our customers and for those customers' business transformation needs. >> Talk a little bit about that vertical specialization. It's something that we don't see very often but throughout all of my conversations today with your executives, IFS executives, with customers, with partners, that domain expertise, really the granularity of the domain expertise is really resonant that IFS has achieved that in those five key verticals in which you have such specialization. >> Yeah, look, I mean, I would love to take credit for having been the person who has done that, but IFS has over the past 35 years, really had this very strong focus. But what actually was important when you try to double a business in the space of four years, not to be tempted to go away from that but actually double down on exactly that and see the opportunity in those verticals and make sure that our customers actually are getting the attention and the functionality they deserve. >> Let's talk about customers. Over 10,000 customers right now. I was also in the keynote this morning where Christian Peterson was sharing that, in its first 18 months, IFS Cloud has over 400,000 users. So the growth is tremendous. The customer loyalty is ostensible in those verticals. Talk about customers and their influence on the company, the direction the technology goes, the evolution, that kind of stuff. >> Yeah, I mean, look, as I said, we are all about the depth of the functionality and that means that we need to listen to our customers, We need to listen what's going on in the industries. We also need to not just listen but we need to think forward. >> Yeah. >> We need to have some thought leadership on what we think is going to emerge and then test that with our customers again. So our customers are at the core of everything we do. When we engage with a customer, we start with trying to understand their business in depth. We've got our own methodology around that and we don't just try to push technology onto them, but we are trying to understand what are their business drivers and then actually try to apply technology to what enables them to deliver on those business transformation objectives they've got. >> What are some of the changes or the waves that you've seen, especially the last couple of years during the pandemic when we saw so many customers pivot, we need to transform digitally to stay alive, and then those that did that well enough to be competitive and to thrive, talk to me about some of the changes as the group's COO that you've seen. >> Yeah, so when you go back, I mean, there's two types of transformation, business and digital transformation but they are the same thing, they're just a different side of the coin. And when I talk about business transformation, what we're seeing a lot is, and there's this big buzzword overtization out there, but customers going service and customers trying to build an end to end business that is more viable, more sustainable, more successful in how they develop great moments of service for their customers, that is something we are seeing a lot. And during this business transformation, digital transformation has become a means to that end. And that is something where customers have matured a lot, where in the past we have seen a lot of the IOT, AI, machine learning, cloud, everything was a means or a purpose in itself and that has changed. It's now become actually a means to an end. It's become a means to actually deliver a business transformation and a business outcome that is meaningful for their customers. >> Has to be meaningful for their customers. I love how IFS talks about enabling your customers to deliver those moments of service. And when we think of, in our consumer lives, many of us flew here, and you think about what's the moment of service for an airline? Well, it's being able to get on that plan on time, have it leave on time and meet my expectations as a demanding consumer. But regardless if we're talking about aerospace, energy, manufacturing, engineering, the customers on the other end expect to have an integrated seamless experience that's not fragmented, that is able to deliver moments of service that then help drive up their revenue. So what IFS is doing is so embedded in what your customers are able to deliver to their customers. >> Yeah, absolutely. And look, if you look at all the things that have to come together to actually have a plane taken off at the right point in time or if you take any other examples, but there's so many things that need to go right. Crew scheduling, you need to have the right crew at the right point in time. You need to have them actually with the right experience to fly the right plane. You need to have airplane maintenance going right to have the plane available at the right point in time and no technical failures and so on and so forth. And we look at that as between customers, the people, and the assets that an organization has, you need to coordinate between all those dimensions in everything you do to make sure that this one moment of service where your plane takes off on time, you actually catch your connecting flight at the other end, that this actually is being delivered. And that's what drives us, that's what customers are driving into our product development, into how we embed AI, machine learning and so on in our technology to make it relevant to exactly that moment of service. >> That's what we as those consumers want. We want relevance, we want personalization, we want that relationship to know who we are and how to serve us best. Let's dig into the Jotun case study. He was going to join us, our CEO was going to join us, couldn't make it. Talk to me a little bit about Jotun, what type of business is it and then let's kind of start unpacking how they're leveraging IFS technology. >> Yeah, so Jotun is the seventh largest paints and coatings manufacturer in the world. And they've got obviously a home decoration part of the business, but they've got an industrial part of the business where one large part of the business is also a marines part. So they actually provide paints, coating, for all sorts of large ships and it's quite astonishing what you learn about that customer. I mean, we are now partnering with them for more than 20 years, so we are very intimate with that customer obviously. But when you see all of a sudden, three, four years ago, they started going onto a journey where they looked at apart from paint and coating, what actually can I provide to my customer in the marine industry to actually make their business more efficient, to actually make it easier for them to get a ship from A to B in an efficient way, in a timely way and so on. And they developed something called Hull Skating Solutions and those Hull Skating Solutions are integrating all sorts of weather data, all sorts of other data and provide them to the marine companies that actually then help them drive this... Well, actually get this ship in a more efficient way from A to B. And at the same time, also where there's predictions as to when you need to clean that ship, and they've got Hull Skating Solutions, which then actually clean the ship automatically as well. So it's quite an astonishing thing for a paints and coating manufacturer to then think about what do I need to know about my customer's business to provide that additional service to my customer? Great solution and great way of dealing with or delivering that great moment of service to their customers. >> Absolutely, the evolution of that business from paint manufacturing into the marine industry is not a stretch based on how you described it, but it's very innovative. How is IFS enabling them to do that and do it well? >> Well, one, they went on a modernization program for all their factories for all these kinds of things that they need to integrate then deliver to their customers. And we are in the central part in being that agile partner that actually delivers those technology solutions that enable them to, well, first of all think about that service, provide that service to their customers and make sure that they run a very efficient, very integrated version of IFS and can actually harmonize globally to make sure that wherever the customer is, they can deliver on that promise. >> Fantastic, let's talk a little bit about from your team's perspective, the go to market. We talked about the five verticals in which IFS specializes energy, aerospace and defense, engineering, manufacturing and there's one I'm missing. >> Utilities. >> Utilities, of course. >> Yeah. >> In terms of the domain expertise, are there vertical teams that are focused? I imagine that there are, talk to me a little bit about that specialization from that lens. So obviously, I mean, there are so many dimensions. There's our sales teams, there's our pre-sales teams, there's our industry teams which actually are working with the customers on receiving their feedback, on actually providing thought leadership and then organizing the feedback loop into our development teams who are providing these solutions then that hopefully our customers will cherish. So we are very specialized in that respect. We are driving the industry specialization. We've got a complete aerospace and defense business unit. We are in the market unit, specializing in the industries where we work in the various different territories with just those industry teams. We've got specialization in the pre-sales teams. So we take that really deep down and very seriously to make sure that whenever we talk to a customer, we also have the understanding and we have also got the curiosity to understand more of the customer's business, and that is something that is part of the IFS DNA. >> It's a differentiating part of IFS' DNA that not only having the domain expertise, and a lot of people talk about, well, we got to meet the customer where they are, wherever they are digitally, wherever they are in business transformation. But you're actually talking the customer's language. >> Yeah. >> By industry, which I would imagine really helps to not only solidify that relationship, but you actually get to really do a double click and get much more tightly connected with the customers and the outcomes that they're wanting to achieve so that those moments of service happen. >> Well, that's so true. And actually this is not just while we are selling to the customers, but it's actually throughout the whole life cycle of this application and the technology in Jotun's case more than two decades. And we've got a lot of customers who are actually that long with us because we don't run away once we've implemented a solution, but we actually stay close to it because first of all, we want to learn from our customers continuously. We want to actually give to our customers also what we are learning outside of the conversations we have with these customers. And we make sure that these customers continuously evolve how they think about their business, how they think about the application of our technology and then in turn, we can actually develop technology again, for their use cases. >> It's a flywheel. >> It's a complete flywheel and that creates loyalty. >> Yeah. >> That actually creates the longstanding relationships we have with many, many of our customers, yeah. >> I was speaking with a number of your executives, Marni Martin was here and we were talking about brand recognition and the loyalty, but that intimate customer knowledge that IFS really works hard to gain with its customers. 'Cause as consumers, we bleed into our business lives and we have very little tolerance, very little patients. I think that was one of the things in COVID that went away. People were just not tolerating this rapid change and we had no choice. But I don't know that patience is going to come back at the level in which we experienced it before COVID. So customers expect businesses and brands to know them and help anticipate what's next for me, how do I get there? And it sounds to me like IFS has really nailed that from a customer relationship perspective. >> As I said, I mean it's really part of our DNA and we try to preserve that culture while we're doubling our business and hopefully, doubling our business in the next three years again, because that is really the secret sauce to being that successful, and not only with our existing customers, but also with the net new customers. And we are driving almost 50% of our revenue, which is very, very much a benchmark in the industry from net new customers that we're winning while we're actually keeping or staying close to our existing customers and try to apply that knowledge to our net new customers. >> Yeah. >> But it's something that we absolutely have to preserve to be as successful as we've been in the past four years, also in the next four years. >> So coming off a great first half in the summer, when I teased Darren, "Any nuggets you want to say?" He said financials for Q3 are coming out in the next couple of weeks. And I said, I imagine that trajectory is up and to the right. >> Yeah. >> What are some of the things, Michael, that excite you for where you've seen this company go in your time there and the rocket ship that it seems to be on today? >> Yeah, look, I mean, what's amazing to me is... And if I look back, I joined four and a half years ago, and only the first one and a half years were under normal circumstances. >> Right. >> The other three years were a major pandemic, now a major war and recession and we've got all sorts of economic and macroeconomic headwinds. And what what impresses me about the company, about our customers, about our employees is the resilience we've got to just carry on with what we're doing. And I mean, I don't give too much away when I say we had a pretty good Q3 as well, and we are looking forward to a really good 2022 as a full year, and there are no excuses that actually the organization makes, it has just taken along. And we are facing the economic headwinds and we are going through that time hugely successful. And I'm very optimistic about the year and about 2023 as much. >> Fantastic, it's kind of hard to believe that calendar year 2023 is literally around the corner. But Michael, it's been great having you on theCUBE. Thank you for coming back, talking about what's going on at IFS from the overall COO's perspective, the customer synergies that IFS has, the work that you do to really get granular in those industries, it's impressive and congratulations on the success. We'll have to have you back next year to talk about what else is new. >> Thank you very much, Lisa. >> All right, my pleasure. >> Thank you. >> For Michael Ouissi, I'm Lisa Martin, you're watching theCUBE's coverage live from Miami on the show floor of IFS Unleashed. We'll be back with our final guest in just a minute. (soft music)