6th YEAR SEASON FINALE: Juan and Tim Rant

[Music] Hello, hello, it's time for cataloging cocktails. You're honest, no BS, non-salesy conversation about enterprise data management. There's many cocktails as possible in hand. -Here we go. -I'm Tim. Hey, Juan. How you doing? Uh, six years, my friend. Six years. I can't believe it. [Laughter] Where are you right now? You're not in Austin right now, right? Let's travel around the world. [Laughter] Next week, you spend more time not in Austin, I think, than in Austin. Yeah, next week I'll be in San Francisco. [Laughter] But yeah, here we are. What are you drinking, man? I'm drinking a, it's very close to a negroni, but instead of being, you know, usually a negroni is 1-1-1, right? And in this, what I did is I, the campari, I did half campari, half Amaro Nano, so it just like-- I need to do more-- It softens it a little bit. So, I-- I can drink now. All right, again, looking to my, what's in my, what's in my bar? This is a Spurnoff Spicy Tamar in vodka. So those who have listened before, you can probably guess where I am if I'm drinking that. And then with liquor 43, and then also a driver-muth. So it's kind of a spicy Spanish Martini's, what-- Chachipito, to-- It's a Spanish Martini. You like it? It tastes good? Oh, yeah. This is a good one. Nice. All right, well, cheers. Cheers. Happy six years. Another great season. This is-- our numbers are off, but this was, I think, a season 11. We'll comment it. Yeah, because at one point we started counting each year as two seasons. Like we would-- Yeah, for sure. --if we were to see it as a season and then like spring as a season. So-- And we always take off for the winter. And we take off for the summer. And then we'll step-- So we want to do like a recap of stuff. But anyways, what's on your mind? 2026 is-- Yeah, we're out way through it. We've had a bunch of amazing guests. But yeah, what's on your mind? Just-- just-- just ran a little bit. Well, first of all, we had some amazing guests this season. I think I was just very-- I was starting to look through all the guests that we had and just looking at all the names of folks that we got to chat with, from Tony and Matt, to Victoria, to Jenna and Amalia, to Anana and Anana. Like we just had somebody good conversation. So one thing that's very top of mind is I continue to feel every day very blessed and happy to be in the market and in the space and interacting with the community that we get to interact with because just the quality of the people, the quality of the conversation, the quality of the thinking going on right now is just so high. And it's exciting to be a part of that with you, Juan. We get to talk to some cool folks. So let's create the list here that we did. So we had Tony Bear, Matt and House Lee, all of us got a corcho, Irina Steenbeck, Plan Gorecho, Viab Gupta, Nashikett Metta, Sadie Haveri, Taiz Cook, Kira Dodson, Kyle Winterbottom, Pete Williams, Jenna Jordan, Amalia Child, Diana Wood David, Victoria Garamond, Bob Sinor, Jason Dor, plus we, and also, Jesus Barraza on the one of our ran sessions. One of our ran sessions. Everything from data catalog, data governance to decision intelligence to, I mean, AI governance and data lineage and ontologies and trends and data leaderships and like what's our CDOs talking about? Obviously, AI is spread across everything. And so this is what I really love about. We've had this opportunity to go talk to so many people. Now, I'll tell you what's on my mind right now. Just I've been on the road for, I'm always on the road. But actually, like I was at our knowledge conference. Just recently, then at Gertner London, and then we, I did this tour kind of through Europe last week. And everybody's still on the basics. Everybody's talking about context is the most popular thing. The proper right, the semantics, ontologies, and love. But wow, people are still on the basics. So I think as the reminder is that we need to get out of our bubble to really understand like where people are today. We know where we want to go. And that's why I think the foundational stuff of like this understanding. What is the business value we're connecting, right? What is the, and having like the basic things we need to go do like, just know what data we have and all that stuff. Like people are still kind of in the very early stages. And I think you see things on LinkedIn and you read things and you read all the blog posts and stuff. And you see all this cool stuff. But if you like, I've been looking, I've been talking to 100, 100 different people in the last couple of weeks. And it's very clear that the maturity level is pretty low. And that's not to say anything negative on what's happening with what people are doing. It's like, there's just so much stuff. And we got to start somewhere. And just, and I think we understand where the destination is, where the vision is. But what really, I think one of the things that we really need to focus on is, I know this is going to sound like a lot of marketing blah, blah, blah. But like a maturity model, a maturity curve. Like I think that's one of the things that we really need to ground to the reality. And not, and when I mean, ground to the reality is like, here are the couple of things that you can do, small things that you can do today that is going to elevate you. And one of the things I don't forget from Juan Gritio said is like, you got to just do this in slices. All right, that's a little bit of a taxi you want to go do. You're going to go do some slices. So that's for me like the thing that's a top of one of the most important things that's a top of mine for me. I think that's, I think that's well said. You know, something that that, that you just went through there, kind of your, your, your, your breakdown of that. It makes me a little worried and a little afraid for, for the industry right now because, you know, a few years ago, we're talking about laying foundations, right? We're talking about you need to have quality data. You need to have data fluency and it, well, we didn't, maybe we said data literacy back then, right? But now it's data fluency, right? But people need to participate around data. We said it's, it's people process and technology, right? Don't pull the ocean, right? Three years ago. And you know what? We were saying it three years before that. And so it's, every year is the year of foundations. You know, it's funny. You go to the Gartner conference every year, right? And every year they go up on the keynote stage and they say, you need to have high quality data. You need to have your foundation. You know, and that's going to what's unlock, you know, you know, maybe 10 years ago was I would try to unlock self-service AI or self-service BI and data-driven culture. Now it's we're trying to unlock AI, right? So, you know, it's, it's, um, fascinating and a little worrying to me that we haven't yet claimed victory on those foundations. And I think for everybody who's listening and, you know, you can look at any of our episodes, they will give you like a frickin' like fitness gym on like ideas of how you can properly set your foundation. Um, we need to make some progress on that and it needs to stick, right? It needs to really stick. And what we have been making progress, but I think it's that that is in a way the, the goalpost moves. And, and it's like, and that that goalpost moving is the hype. So, so we are, we're, we're, we're progress, but then, but it's not like, in by way, it's not like the goalposts, like just moves further away. Like it's in the, and it's probably in the same direction, but maybe just, oh, now it's not, not in front of you, but it's above you or it's on the side a little bit. And I'm like, wait, wait, hold on, but, but, so we were start chasing the next thing. And I'm like, let's speak. Let's also, we go, wait, wait, wait. There's the foundation stuff, and like, where are we headed? Now, the second thing that's really top of mind and everything, and from all the conversations we had, we, we've had on the podcast and also with customers and stuff is that it is, we need to understand that the destination is not just about creating data and creating AI ready data and creating context and having well-governed data. Like that is not the destination. That is a means to the end. And this is why I've been talking so much about we should really kind of be focused for this work at the center and so forth. But actually, what I mean that, oh, work at work isn't, we are, we're at least to be at the center. It's really about, we need to get people who work in the analytics world, the data analytics world, and people who work in the operational world, and they need to sit together same table. And these are people who are running, who are running, quote unquote, your back off. of your business. And then the analytics is like, "Well, how are we putting together so we can do more of our better work?" And part of that, something maybe less back office, but more revenue generations, like when you're talking to your sales teams, right? So your marketing teams and stuff, like how do we get, who are doing operational stuff? Day-to-day, and your data analytics teams, let's sit them at the same table. And that is something that is still lacking. And honestly, I'm very lucky, I've been burdened about this before, but I've gotten out of my data analytics bubble without being at service now, and I'm just interacting with so many people on the operational side. And I've actually now had the opportunity to facilitate these conversations of saying, "Hey, you two don't talk to each other. Let's kind of sit down." And it's just like, "Oh, yeah, that's interesting. We should talk more. We should talk more." That is what's just, and I feel that we're heading there. We're seeing more of that. But that's my big call out for everybody right now. >> Yeah, well, and going back to what you said just at the beginning of that, I do think you're right that the bar keeps on changing, right? And we start to make progress towards something, like data enablement within the organization, and then AI hits, right? And now all of a sudden, we have to somehow make our AI foundations ready for all these things we want to do with AI, right? So now it's not just about data governance, right? Like for example, we talk to Victoria Gammerman and we talk to Cara Dodson, and I feel like it came up in a couple other conversations. Oh, now it's not just data governance, it's AI governance, right? And now you got to think about how that fits in, and can you use the same committees, or do they have to be different committees? Can you use the same policies or the different policies? But do I even get more budget? Do I get to hire more people? Now that AI governance is part of my mandate, right? So, you know, the scope is increasing. I think that's a big aspect. And the change management required is increasing, right? Because now it's not just about the dashboard, it's about the conversational interface, it's about the apps that are being built, it's about the GPDs being customized. So, you know, we talked to Bob Siner, for example, and he talked about how literally one-third of the data catalyst equation is change management, and how critical that's now becoming, where it's not just about laying the data foundation anymore, it's about actually enacting change in the organization, and I'll connect that to what you're saying about, about, you know, bridging with the operational side of the business, right? Because we don't get to live in our analytics bubble if we really want to make an impact on the change in the organization. We have to reach out and connect to work hand in hand with the line of business. - The change management is one of those things, I mean, Bob Siner brought it up really nicely in his chat that we had, and actually there's some looking up on our notes here, his formula, right? There's like, well, the three Cs, right? - The data catalyst cubed, right? - And if one of these things is not there, then it almost applies at zero, right? So, the change management is one of the most under-invested pieces right now. So, you find it right now. - I told it before you there. - The data governance plus change management, or, no, I'm sorry, times, right? - Hi, yeah. - Data governance, times change management, times data fluency. - Exactly. So, if you don't have any of that stuff, then you're actually not making the change with the data. And by the way, the change management piece, right? That's not just about the data analytics. It's also kind of how this is all getting connected with the operational side of the world. And actually, recently at, I'd gardener what a presentation was on, which kind of really clicked for me. It was like, there's all this, we call it data governance in the analytics world, but there's quote unquote operational governance more on like, probably the business doing it. And they don't call it governance, but they're still doing those types of things, right? And same thing happens with AI governance, right? So, there's like, this governance party is just growing. It's gonna get bigger and bigger. So, this is why it's so important right now, but now this is where we need to really think about it. It's like, okay, how does this actually, how is this being governed today? And I think one of the, I wrote this in the recent pieces, we, I wanna challenge people, I wanna people like homework is, do the life, the life in a piece of data. So, follow a salesperson, write something in their CRM. Okay, let's go follow that, right? And let's go follow that opportunity. So, they added an opportunity inside of their CRM. Where does that all go flow on that system? How does that land? Where does that go? It ends up, it ends up in your, supposedly, systems and all these people touch it. And all these changes occur. It lands in your data warehouse and your data lake. And the litus get built on this stuff that somebody again is looking at that stuff. And then that other person is making a decision, we're just, let's go follow that piece of it. I think that would be a fascinating experiment that experiment and experience we have to go through. >> Yeah, that's true. And it's different than just like data lineage. We're just looking at data transformation and things like that. You're talking about like truly, how does the data, what is the data lifecycle? >> It's exactly, that's the data lifecycle. And in a way, it's also data lineage, but it's not just the data lineage that we see from a data lineage perspective. It's the lineage and the lifecycle of that data across the entire organization and not just technical. Oh, it moved from this system to this system, but there's also, there are these people who touch it for some reasons, they make changes for it manually, whatever. And they're looking at it for what reasons, right? And what decisions are they making on that, that may not be documented, like, that's something we should go follow. I mean, and all these decisions we put are making, this goes back into decision traces and all this context graph and all that type of stuff. Like that's the really stuff we should be going following. And also, at the end of the day, we want to be able to kind of understand what are these, what are these business processes and how they do that? Because later on, that's what you understand, like, oh, wait, that wasn't efficient. Like, why did we go do that? Maybe it's a thought that we can go improve. I think that's kind of that first map that we want to go understand. - Yep, agreed. And you mentioned data, right? And we got Chris here, leaving a nice little comment, knowledge lineage. You just mentioned about knowledge and context, right? And I think that was another key theme that I think we heard a lot in these episodes was around how data people are starting to think about kind of knowledge and context and semantics and ontologies in a more direct way. And of course, needing to understand the life cycle and the lineage of those types of aspects in our organization, which are probably more wild, wild west than even our data is. - This is why I'm really excited of knowledge, whatever we're talking about, has now getting the spotlight when I think it deserves. But then also I'm like, wait, let's pause because it's not the end goal either. It's not forget, right? It's another means to it end. So that's the important, because I mean, I also wrote this, it's like, we were talking about, well, we live in this data first world, we should move to a knowledge first world, we should. Well, let's not forget that it's not the only thing. And I think this is what we need to get out. - We'll all means to the end. - And then we'll talk about those means, right? There was Bob Siner on here right now. Data catalyst cubed, data governance times change management times data fluency. And if one of those is zero, the whole thing goes to zero. - And it's not invasive data governance. - Mm-hmm. All right, well, what else is on your mind? - Just keeping on going on with knowledge, semantics, context, two things. One is, and this is a little bit more of a broad of thematic than necessarily a specific in our sessions, even though I think it came up a few times. Obviously, context is the word of 2026. So that comes up over and over again. - How many people have, well, many people are now shifting into that. Here's the honest OBS, everybody's now a semantic expert and getting to a context expert, and everybody's now a. - Every company is a context layer, right? - Yeah, we're a platform system engine. - Well, it's exciting, you know. We're talking about the next thing up, which is good. I mean, Juan, you've been talking about knowledge and context for a long time, which is fun. And I've been talking about context wars, right? That like that, we're gonna get into a future where everybody wants to own the context, right? Every vendor is like, oh, where are your context layer? And like, boom, here we are. 2026 is the year of the context wars. - We should go find this because we have all the evidence. We'll go find the first time we talked about context wars. I'm really excited. - Yeah, I'm trying to remember when it was. I feel like it was maybe 2024, something like that. A couple of years ago. - Probably earlier. - Well, look. - We should have this transcript. - Yeah, we should try to find the lineage of that 'cause I remember we talked about knowledge first. That was kind of a big thing. And then it context wars was after that. But I think that's obviously that's exciting. Everybody's talking about context. You know what else everyone's talking about? Antologies. - That is true. And that's a big episode. For an episode, the one with Oscar Corteur, like I mean, he is the guy, the reason why I got inside of everything I do. He was the first person who introduced me to semantic web as 2005 now. So that's a great episode about kind of dive it into the, the old school reality of an old school. of ontologies. And that ontologies aren't new, right? So learn your history, not to, you know, be pedantic or anything like that, but because there's a lot to learn from history, right? What went well, what didn't go well, and the best practices, and so on. Another follow-up on that is like the episode we did with Nashek Ket, Reddough, like he's had, he has been somebody who's done so much experience on like implementing ontologies and knowledge graphs inside the organization and had so much success around this stuff. It's like that's a big example. If you want to like have an experience, have a have a hear the conversation directly from a data leader who has done this and talked about the amount of money, the tens of millions of dollars sold because of how his investments within semantics and knowledge are, that's an excellent episode to go listen to right there. I agree. All right, Tim, what are we, what are we going to do next? You know that we're like, we're just kind of, as always, we're just kind of winging it here because people want to go listen to the episodes, like listen to all these episodes. These are all fantastic, these are all fantastic people. Yeah, it's really hard to kind of, we can't do it service to like talking about everybody because there's like so much stuff, we're then just talking so many hours, I'm about everybody who's talking about so. Yeah. Let's talk about what's next. What's on your mind about what should we be doing next? Not just for the podcast, but also just in general for the, for the industry. That's a good question. You know, I think one thing that's very top of mind for me and I wonder if we can find some guests that can actually go into this so that we can kind of dig into it together. I want to see more examples, public examples of folks putting not just AI into production because I think we're seeing a pretty strong way of an AI going into production, right, of around, you know, obviously productivity based applications, but also starting to use it for customer service for, you know, sales opportunities for you're seeing a lot of different kind of vertical applications of AI now, but in use cases where some of the non-determinism is okay, right, I think those are the use cases that we're especially seeing in production now, right, where it can be a little fuzzy, it can be a little off. I want to see more examples of folks really doing knowledge and context management at scale, incorporated into their AI applications that are in production. And I'm sure there's folks out there. I'm sure some of you listening probably know of some of these folks that have started to roll out not just, you know, kind of basic generative AI applications, but like really deeply embedding context and knowledge in those applications. I want to bring more of those stories to life. So that's one thing that's very top of mind to me. Yeah, that's good. I like the, the the bringing things to production and I want them is not just an application or use case in production, but it's like doing this at scale, like, like how we're able to, we have the foundation and how not with this foundation, we were able to get all these multiple use cases one after the other one because it's leveraging the foundation. Right. So that's one I love to go. So people listening, if you want to, if you have good use cases, a kind of example to do this, like please, please shout out. Yeah. And part of that can be, you know, Bob mentioned, you know, context catalogs is just kind of an off hand comment here. I mean, one of those things is, you know, incorporating your catalog and your governance into, you know, we've got some customers that are starting to do that. I know there's probably some other people in the industry that are starting to see that where you're actually tying the context that's in your catalog or creating a catalog specifically around context and incorporating that into your AI applications. What I want to hear more is about change management. Because that's a topic that has come up a lot. I mean, with Bob Siner, but I think it's something that we're missing in our industry. We talk about it. We know we need it. But we, I don't, I haven't met people who have kind of, we can talk like, very heavily, very, they've actually been able to share their experiences of what works and what does it work and what type of organizations, the different cultures about how we do this change management. Like, I think that's something that we really need to go learn more. I personally need to learn more. And I think that's something that'll be very, very valuable. Yeah, no, I think that was good. And, you know, kind of related to that, you know, I think we had a couple of good episodes this season, you know, from Kyle Winterbottom and from Pete Williams, for example, where it talked about how a lot of times there's these like board or leadership mandates, which force certain behaviors. And I think related to change management is also like, how do you manage the board? How do you manage leadership to create an environment where you can be more successful with your data strategy? And so, you know, kind of, I think a couple more episodes and guests that can dive into that topic, you know, I think would be great as well. Another one is, I'm actually looking at kind of our notes here. Victoria, a government suggested we should invite who should invite next. Someone who has used AI to extract knowledge in these invisible processes. I think so. So we wanted to be able to also think about how to connect the whole analytic world and operational world. We want to talk about decision traces and context. I was like, how are we managed? How are we extracted and kind of formalizing all that knowledge, all that business process knowledge? So people were working on this, I think that would be fascinating because I want to be able to tap into people's heads and catalog what's whether they do it in all that tacit knowledge. People have been actually trying to do all this stuff. So that's another one for sure. And then yeah, Chris, actually Chris, it's been a while. We didn't to catch up. Yeah, there's a few folks that we've been chatting with on episodes a few years ago that I think have made a lot of, not a lot of cool stuff and we need to catch up. Yeah, Chris, I wasn't wondering, you didn't reach out to me on kind of sad. That's a live guilt trip there. Here's another one. Organization design development and change management for sure. Yeah, that's a long thing. Also that whole organizational design. That's another, that's another interesting topic is we've talked about how people are doing kind of centralized decentralized, federated embedded teams. How are things changing now with AI? So you are people we're talking about, oh, everybody's going to be a manager of the AI agents and like we're seeing a lot of layoffs happening. We're going to do all these changes. Like I'm very curious to know what, what is like the current organizational structure that's happening. That's another interesting topic. I'd be very, I'd love to kind of dive into more. Yeah, no, I agree with that. I've been seeing a lot of social media and articles of people talking about like when AI starts to come in and become a part of, let's even just focus on software engineers for a second. If it starts to become a major part of how you're developing software, how does that affect, how does that affect org structures too? For example, do you need less management hierarchy? Do you need, can you have one engineer, can you have a lot of engineers per product manager? Anyways, it's interesting to think about what changes, can organizations get flatter? Can you have less of a certain role? That's what I think. Yeah, that's exactly the same. By the way, I see, Shahar commented here, "Wildred from history, you can just repeat the same mistakes again and again." Anyways, Shahar mentioned that because I was, I think, one last week or whatever, I forget two weeks ago, and he invited me to his new, I forget the name, the helicopter podcast. Oh my God, I saw the picture of you. Anyway, he just texted me right now. He's like, "Oh, I can speak about change management." And Shahar said we've been wanting to have the podcast, so perfect. We got our change management topic coming up soon. Shahar, thank you so much. Excited for that. Excited. Thank you so much for inviting me to be on the in the helicopter because you changed my life with that. It was such an amazing life-changing day and a bend for me. And I can't wait to listen to that podcast. But it was just, it's just crazy that I'm like, we're talking about data and then I'm like looking over the world like this stuff and like, "Wow, anyways." How do you get the microphone? Is this a really good like noise? And then the cool thing is that I had a helicopter listen afterwards and I'm like, "How the heck can you have to think and not think about this stuff?" And I'm like, "How the heck is he doing this?" Like, having this conversation, but anyways. But yeah. Anyways. Have you ever seen the, I forget if it's a podcast or if it's just video clips, the subway takes that guy Karim who like rides on the New York subway and he always has like celebrities with him and stuff like that? You know what I'm talking about? I don't know if anybody's listening, who knows about Karim Rama and he does these and he always has like a celebrity with them and I don't know, it's like the idea of like, you're riding a helicopter, you're riding the subway, you're like, I don't know, it's just kind of a fun idea. I'm looking at your Shahar's now, he says, "My friend is a director in Big Tech company, he told me, "Shahar, I built AI agents that asked my team for status updates on their project so they don't forget to send it." And then he said, "You realize that your team has agents responding to your agents and nobody knows what's actually happening, right?" (laughing) - Do you know what that's called? It's called bullshit fabric. (laughing) - Thanks you my friend, Jar. We're really excited. Thank you for changing my life that day. All right, okay. Anything else or we just know where I'm going here? - What else? Dude, we forget anything? Any other major topics we should call out to? - All right, folks listening just, I mean, here's another thing. For those of you who are listening, we've been doing this for six years and people ask us like, why? Actually, in January, I was with Joe Reese and Joe's, like, you guys should just stop the podcast. Like, I'm like, just do something else. And I'm like, you know, come here, thank you. - You've actually told that to a few people. I was like, you know, we've known this for six years. Maybe it's time for us to do something different. And every single person has told me, why? Like, why would you stop? - Well, exactly. It's like, I wonder about this. And I'm like, I don't know, which is not fun. This is not, or I mean, this is, we have no, we keep it super simple. Keep it. - There's always more cocktails and there's always more stuff to talk about, right? - Yeah, so I wonder where else. So people want to have any ideas what we should go do. And one thing I would like to go do, for example, is maybe some panels or have two guessing time. - Yeah, can we change the format maybe a little bit? - Hmm. - Makes it a little bit. - Yeah. - Folks have any comments, thoughts about that stuff, please? And also, if you want to be on the podcast, let us know. We get a lot of requests in folks listening. I'm sorry, for some of you, I was like, a lot of PR firms, like, oh, you should have this person. You know, I'm like, yeah, maybe, but I really want to kind of have people that we really know part of the community. Sorry. So folks who are listening, who've been listening for a while, if you really want to be part, just reach out to us. We really want to, I mean, we keep doing this because we have thousands of thousands of people who listen to us every single week. It's amazing. Thank you. So thank you, thank you, thank you for everybody's listening. I know there's a handful of people who are watching us live right now. You are all amazing. Like, I mean, I, I, I, I speak from myself, I'm sure, for you two to have a lot of time. It's like, we are super freaking lucky to have to, you've elevated our own status here too. You've elevated our own ego. Thank you, because that's not, I will not deny that. Honest OPS is great. It feels awesome. It feels awesome to go out and comfort to the people like, look at you and want to take a picture of you. Like, that's super cool. It was hard to believe that, you know, this all started with just turning on Zoom and, and, and, and hanging out with some pandemic. Very pandemic. Yeah. Well, that part was a little unique. But I guess thank you, pandemic. Yeah. Juan, you got any good plans for this summer? More travel. Yeah. More travel. Snowflake Databricks. So June, all right, just quick. June, I'll be, I'll be in snowflake summit. And that'll be a Databricks. And that'll be in Guadalajara, Mexico. So that's what that's June. Something will happen July, some of the August. I'll plan to be a big data London in September. Yeah. Things will happen. But, and then I will, I will take time off and just be with disconnect. So we also need to figure out where to start restart the podcast. We'll probably do some ran sessions in the middle. Yeah. We'll keep it, keep it fresh, keep it exciting. Yeah. You know, for me, I have a little less travel this summer. Usually I'm, I'm road-waring with YouTube, but I'm traveling a little less this summer. I'm actually focused on trying to move into my new house. And so you're going to see some different background behind me soon as I move into my new office. So stay tuned on that. All right. Tim, six years, which is, and I think that means that we've officially been working for almost seven. It has been a pleasure to do this with you. And I think it's, it's just a natural thing. I expect it to, I expect it us to do this every week. And everybody listening. So thank you, thank you, thank you to everybody listening to all our amazing guests and to you, my friend. Cheers. Cheers, Juan. And cheers, everyone. Have a great summer. Cheers. Well, we'll, we'll, we'll still be around. We'll be follows on LinkedIn. See us at conferences and we'll be doing some ran sessions. Let's keep the conversation going. Cheers. Cheers.