6th YEAR SEASON FINALE: Juan and Tim Rant

Speaker A: Hello, Hello. It's time for catalog and cocktails. Your honest, no bs, non salesy conversation about enterprise data management with as many cocktails as possible in hand. I'm Tim. Hey, Juan. How you doing?

Speaker B: Uh, six years, my friend. Six years.

Speaker A: I can't believe it. Where are you right now? You're. You're not in Austin right now, right?

Speaker B: Just traveling around the world. Around the world.

Speaker A: Next week, you spend more time not in Austin, I think, than in Austin.

Speaker B: So next week I'll be in San Francisco, but, yeah, here we are. What are you drinking, man?

Speaker A: Uh, I. I'm drinking a, uh. It's very close to a Negroni, but instead of being, you know, usually a Negroni is one, uh, one. One. Right. Uh, and in this, what I did is I. The. The Campari, I did, um, uh, half Campari, half Amaro Nonino. So it just, like I need to do it softens it a little bit.

Speaker B: So. So I have. All right, again, look into my. What's in my. What's in my bar. This is, uh, a Smirnoff Spicy Tamarind 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, uh, a driver mouth. So it's a kind of a spicy Spanish martini, is what? Um, spicy Spanish martini.

Speaker A: You like it? Tastes good.

Speaker B: Oh, yeah. This is a good one. All right, well, cheers.

Speaker A: Cheers.

Speaker B: Happy six years.

Speaker A: To another great season.

Speaker B: Another great season. This is. Our numbers are off, but this was, I think season 11 is what we're calling it. And then.

Speaker A: Yeah, because at one point we, um, we started, uh, counting each year as two seasons. Like, we would, you know, like it was a season. And then, like, spring is a season, so. And we always take off for the. The winter, and we take off for the summer, and then let's.

Speaker B: Yep. So we want to do, like, a recap of stuff. But anyways, what's on your mind? 2026 is camp. Yeah. It's. We're halfway through it. We've had a bunch of amazing, uh, guests. But. Yeah. What's on your mind? Just dump. Let's rant a little bit.

Speaker A: Uh, well, first of all, we had some amazing guests, uh, this season. I. I think I was just very, you know, I was starting to look through all the guests that we had and just looking at all the names, you know, of folks that we got to chat with, um, you know, from. From Tony and Matt to Victoria to Jenna and Amalia to. On and on and on, like we just had so many good conversations. So one thing uh, that's very top of mind is um, 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, the quality of the people, the quality of the conversations, the quality of the thinking going on right now is just so high. And uh, and it's exciting to be a part of that with you Juan. We get, we get to talk to some cool folks.

Speaker B: The. So let's create the, the list here that we did. So we had Tony, uh, Tony Bear, Matt Housley, Oscar Corcho, Irina Steenbeck, Juan Goricho, uh, Vaihab Gupta, Nashiket Meta, uh, Sadie have very Thais Cook, Kira uh, Dodson, Kyle Winterbottom, Pete Williams uh, Jenna Jordan, Amalia Child, Diana with David Victoria Gamerman, Bob. Bob Signer, Jason Doerr plus we. And also Jesus uh, Baraza. On the uh. On one of our rants.

Speaker A: On one of our rants.

Speaker B: Yeah. Everything from data catalog, data governance to decision intelligence to I uh, mean, I mean AI governance and data lineage and ontologies and trends and data leaderships and like what. What's our CDO is 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. Um, 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 GNER London and then we. I did this uh, tour kind of through Europe uh last week and everybody's still in the basics. Everybody's talking about context is the most popular thing. The right semantics, ontologies and love. But wow, people are still in the early in on the basics. So I think as the, the reminder is that we need to get out of our bubble to really understand like where people are today. We know where we, where we want to go. And that's why I think the foundational stuff of like just understanding what is the business value. We're connecting right? What is the. And having like the basic things we need to go like Noah 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, I've talking to hundred, hundred different people in the last couple weeks. And it's very clear that the maturity level is pretty low. And, and that's not to say anything negative about what's happening with what people are doing is like, there's just so much stuff and we got to start somewhere and just. And I think we understand where the dest is, where the vision is. Uh, but what really, I think one of the things that we really need to focus on is, 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 stuff that we really need to ground, uh, to the reality. And, and not. And what I mean, gradual 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 uh, one of the things I'll never forget from Juan Goricho said is like, you got to just do this in slices. Uh, 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 on top of one of the, one of the most important things on top of mind for me.

Speaker A: I think that's, I think that's well said. Um, um, you know, something, that, that, that what you just went through there, kind of your, your, your, your breakdown of that, it makes me a little worried and a little afraid, uh, for, for the industry right now. Because, you know, uh, 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 blow the ocean, right? Three years ago. And do you know what, we were saying it three years before that? And you know what, we were saying it three years before that. And you know what, we were saying it three years before that. And so 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. And that's kind of what's unlocking, you know, you know, maybe 10 years ago, it Was we're trying to unlock self service AI or self service bi and data driven culture. Now it's, we're trying to unlock AI. Right. So, uh, you know, it's, it's fascinating, um, 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 freaking like fitness gym on like ideas of how you can properly set your foundation. Um, we need to make some progress, uh, on that. And, and it needs to stick, right? It needs to really stick.

Speaker B: And. But we have been making progress, but I think it's that like is in a way the, the goal post moves and, and it's like that goal post moving is the hype. So, so we are, we are progress. But then it's not like, by the way, it's not like the goalpost like this moves further away. Like it's in the, it is 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 what. So we were start chasing the next thing and I'm like, let's speak, let's. Let's also wait, there's the foundation stuff and like where we're heading now. The second thing that's really top of mind and everything from all the conversations we've had on the podcast and also with customers and stuff is that 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. 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 refocus for this work at the center and so forth. But actually what I mean that uh, oh, work at work isn't working, needs to be at the center. It's really about, we need to get people who work in the analytics world, in the data analytics world and people who work in the operational world and they need to sit together at the same table. And these are people who are running, who are running, quote unquote, your back office of your business. And then the analytics is like, wait, wait, 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, revenue generations. Like you're talking to your sales teams, right to your marketing Teams and stuff. Like, how do we get who are doing operational stuff day to day? And you're in your data analytics teams, let's sit them at the same table. And that is something that is still lacking. And, and honestly, I feel very lucky. Like, as I mentioned, I've written about this before, but, like, 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 not 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 like that. That is what's interesting. And I feel that we're, again, we're heading there, we're seeing more of that, but that's my big call out for everybody right now.

Speaker A: Yeah, well, and going back to what you said just at the beginning of that, I do think you're right that the, um, the bar keeps on changing, right? Like, and, you know, we, you know, we start to make progress towards something, right? Like data enablement within the organization and then AI hits, right? And now all of a sudden we have to, 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 talked to Victoria Gammerman and we talked to, um, Kara Dodson, and I feel like it came up in a couple other conversations. Uh, 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? Are they 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, the scope is increasing. Uh, I think that's a big aspect. Um, 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 GPTs being customized. So, you know, we talked to, um, you know, uh, Bob Seiner, for example, and he talked about how literally one third of the data catalyst equation is, uh, change management, uh, 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 uh, about you uh, 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 and a change in the organization we have to reach out and connect and work hand in hand with the line of business.

Speaker B: The, the, the change management is one of those things that I mean Bob Steiner brought it up really nicely uh, in his conversation in the chat that we had and actually there's, I'm looking up in our notes here right his formula right there's like um, well the three C's right there.

Speaker A: The uh, the data catalyst cubed, right.

Speaker B: And, and if one of these things is not there then it all multiplies at zero.

Speaker A: Right?

Speaker B: Yeah so, so the, the change management is one of the most un, Most under invested pieces right now. Right so or just you found it right?

Speaker A: I bolted it for you there. Data governance plus change management plus or no, uh, I'm sorry. Times. Right. Uh, Data governance times change management times data fluency.

Speaker B: Exactly. So if you don't have any of that stuff then, then you're actually not making the changes in view of data. And by the way the change management piece, right that's not just about the data Linux. It's also kind of how this is all getting connected with the operational side the world. Um and actually when it recently at ah, at Garter one of the presentations I saw which kind of really clicked for me was like there's all this, we call it data governance in the analytics world but uh, there's quote unquote operational governance more on like how every side of the business is doing it and they don't call it governance but they're still doing those types of things. Right. The same thing happens with AI governance right. So there's like this governance party is just growing, it's going to get bigger and bigger and uh, so this is why it's so important right now. But now this is where we need to really think about. It's like okay how, how does this actually, how is this being governed today? And I think one of the, I wrote this in recent pieces we uh, I want to challenge people. I want people like homework is do the light the life in a piece of data. So follow a uh, salesperson writes 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? Um, it ends up in your systems and all these people touch it and all these changes occur. It lands in the, in your data warehouse, in your data lake. Analytics get built on this stuff that, that somebody again is looking at that stuff and then that other person is making a decision or just let's go follow that piece of it. Uh, I think that would be a fascinating experiment. That experiment and experience we'd have to go through.

Speaker A: Mhm. Yeah, that's true. And it's, it's different than just like data lineage where you're just looking at like data transformation and things like that. You're talking about like truly, you know, how does data, uh, what is the data life cycle?

Speaker B: That's exactly, that's a data life cycle. And it is in a way it's also data lineage. But it's not just the data lineage that we see from a data analytics perspective. It's the, the lineage and the lifecycle that data across the entire organization. And not just technical, oh, we move from this system to this system. But there's also, there are these people who touch it for some reason. For what reasons? They make changes for it manually, whatever, and they're looking at it for what reasons. Right. And what decisions are they making out that may not be documented? Like that's something we should go follow. I mean, and all these decisions people are making and this goes back into decision traces and all this context graph and all that type of stuff. Like that's really something we should be following. And also at the end of the day we want to be able to kind of understand what these um, what are these business processes and how they do that. Because later on that's what you understand. Like oh wait, that was inefficient. Like why do we have to go do that? Maybe it's stuff that we can go improve. I think that's kind of that first map that we want to go understand.

Speaker A: Y. Agreed. Well, and you mentioned data. Right? And uh, we got Chris here leaving a nice little comment. Knowledge lineage. Uh, you just mentioned about um, about uh, knowledge and context. Right. And I think that was another, um, that was another key uh, theme that I think we heard a lot in uh, in these episodes was around how data people are starting to think about kind of knowledge and context and semantics and ontologies in, in a more direct way. Um, and, 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 the.

Speaker B: This is why I'm really excited of uh, knowledge. What I've been talking about has now getting uh, the spotlight what I think it deserves. But then also I'm like, but wait, let's pause because it's not the end goal either. Let's not forget. Right. It's the, the, the the it's another means to an end. So that's the important. Because I mean I also wrote this as like we were talking about well we live in this data first world. We should move to a knowledge first world. We should. But let's not forget that it's not the only thing and I think this is. We need to get out all means

Speaker A: uh to the end. But it's good that we're talking about those means. Right. Uh, there's Bob Signer on there, on here right now. Data Catalyst Cubed Data governance times change management times data fluency. One of those are zero. The whole thing goes to zero.

Speaker B: And it's not invasive Data governance.

Speaker A: Mhm.

Speaker B: All right, well um, what else is on your mind?

Speaker A: Just keeping on going on with knowledge, semantics, context. Two things. One is uh, and this is a little bit more of a broader thematic than necessarily a specific. Although uh, in our, 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.

Speaker B: Um, how many people have uh, well, many people are now shifting into that. Here's the honest obs. Everybody's now a semantic expert and get into context experts.

Speaker A: And everybody's now every company is a context layer. Right.

Speaker B: Platform system engine.

Speaker A: 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. Um, which is, which is fun. And I've been talking about context wars, right. That like that we're going to get into a future where everybody wants to own the context. Right. Every vendor is like, oh, we're your context layer. And like boom, here we are. 2026 is the year the context wars.

Speaker B: 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.

Speaker A: Yeah. I'm trying to remember when it was. I feel like it was maybe 2024 or something like that couple years ago, probably earlier.

Speaker B: Was it okay, you can have this transcript. Yeah.

Speaker A: We should try to find the lineage of that because I remember we talked about knowledge first that was kind of a big thing. And then we kind of. And then context wars was after that. Um, but I think that's. That's obviously, that's exciting. Everybody's talking about context. You know what else everyone's talking about ontologies.

Speaker B: That is true. And that's a hard. That's a big episode, important episode. The one with Oscar Corcho. Like, I mean, he. He is the guy, the reason why I got in inside of everything I do. He was the person who introduced me to semantic web as 2005 now. So that's a great episode, uh, about kind of diving into the. The old school reality of. Of ontologies. So.

Speaker A: Yeah. And that ontologies aren't new. Right. So learn your history. Not, not to, you know, 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.

Speaker B: And another follow up on that is like the episode we did with, uh, Nasha Kit Redo. Uh, like, he's had. He's. He has been somebody who's done so much experience on, like, implementing ontologies and knowledge graphs, uh, 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 it. Have an experience, have. Have a. Hear the conversation directly from a data leader who has done this and talk about the amount of money, the tens of millions of dollars sold because of how his investments within semantics and knowledge. That's an excellent episode to go listen to right there.

Speaker A: Yeah, agreed.

Speaker B: All right, uh, Tim, what are. What are we. What are we gonna do next? I don't know. We, you know that we're like, we're just kind of, as always, we're just kind of winging it here because. But, uh, people want to go listen to the episodes. Like, listen to all these episodes. These are all fantastic. These are all fantastic people we have. It's really hard to kind of. We can't do good service to, like, talking about everybody because there's, like, so much stuff. We end up talking so many hours about everybody. We talk about, spoken about. So, yeah, let's talk about what's next. What's on your mind? About what. What should we be doing next, not just for the podcast, but also just in general for the. For the industry.

Speaker A: 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. Um, I want, I want to see more um, examples, public examples of folks, uh, putting um, not just AI into production because I think we're seeing a pretty strong wave of AI going into production right around obviously productivity based applications, but also starting to use it for customer service, for sales opportunities. You're seeing a lot of different vertical applications of AI now. Um, but in use cases where uh, 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 uh, knowledge and context management at scale, um, incorporated into their AI applications that are in production. Uh, 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 kind of basic generative AI applications but really deeply embedding context and knowledge in those applications. I want to bring more of those uh, stories to light. That's one thing that's very top of mind to me.

Speaker B: That's good. I like uh, 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 of these multiple use cases one after the other one because it's leveraging the foundation. Right. So that's what I love to go. So people listening, if you want to, if you have good use cases and kind of examples to do this, like please, uh, please shout out, you know,

Speaker A: and part, part of that can be, you know Bob mentioned, you know context catalogs is just kind of an offhand hand comment here. I mean one of those things is, you know, inc. Your catalog and your governance into. We've got some customers that are starting to do that. I know there's probably some other people in the industry 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.

Speaker B: 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 Steiner. But, but I think it's something that, that we're missing in our industry. We talk about it, we know we need it, but uh, we, I, I, I, I haven't Met people who have. Who've kind of. Who can talk like very heavily, very uh, in, in. In. In. They've actually been able to. Can share their experiences of what works and what doesn't 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 about more. More. I personally need to learn more and I think that's something that'll be very, very valuable.

Speaker A: Yeah, no, I think that was good. And you know, um, 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? Uh, to. 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, uh, you know, I think would be great as well.

Speaker B: Another, Another one is, um. I'm actually looking at kind of our notes here. Victoria Government suggested we should invite. Who should invite next someone who has used AI to extract knowledge and these invisible processes. Processes, I think so if we wanted to be able to also I think about how to connect the whole analytic world in the operational world. Um, we want to talk. We talk about decision traces and context. Like how are we man. Like how is that be managing? How are we extracting that kind of formalizing all that knowledge? All that. All that business process knowledge? So people who are working on this. I think that would be. That would be real fascinating because I want to be. How do we tap into people's heads and catalog what's. What are they doing the. All that tacit knowledge. Uh, people have been actually trying, trying to do all this stuff. So that. That's another one for sure. Yeah. And then, uh. Yeah, Chris. Actually, Chris, it's been a while. We did need to catch up.

Speaker A: Yeah. Ah, yeah. There's a few folks that we chatted with, uh, on episodes a few years ago that I think have made a lot of. Done a lot of cool stuff and. And uh, we need to catch up.

Speaker B: Yeah. Chris, I was in London. You didn't reach out to me. I'm kind of sad.

Speaker A: Um, that's a live guilt trip there.

Speaker B: Here's another one. Organization design development and change management for sure. Yeah. That's the one thing uh, 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, with AI? So you are people we're talking about, oh, everybody's gonna be a manager of their AI agents. And like, we're seeing a lot of layoffs happening. We're gonna do all these changes. Like, I'm very curious to know what, what is, like, the current organizational structure that's happening. Uh, that's another interesting topic. I'd be very. I'd love to kind of dive into more.

Speaker A: Yeah, no, I agree with that. And you know, I've been seeing a lot of, you know, social media and articles of people talking about, like, when AI starts to come in and become a part of, you know, let's even just focus on software engineers for a second, right? If it starts to become a major part of how you're developing software, um, how does that affect, um, how does that affect org structures too? Right? Like, for example, do you need less management hierarchy? Do you need, you know, can, can you have, you know, one engineer? Uh, you know, or, you know, can you have a lot of engineers per product manager? Uh, you know, anyways, it's interesting to think about, like, what, what changes? Uh, you know, can. Can organizations get flatter? Can you have less of a certain role? You know, that sort of thing?

Speaker B: Yeah, it's exactly. By the way, I see Shahar commented here, uh, why learn from history where you can just repeat the same mistakes again and again? Might be fun. Uh, but anyways, Shahar, because I was, uh, last week or whatever, I forget, two weeks ago, and he invited me to his new, uh, I forget the name, the Helicopter podcast. Uh, so.

Speaker A: Oh, my God, I saw the picture of you.

Speaker B: Oh, my God, I can't wait for you. Anyway, he just texted me right now. He's like, oh, I can speak about change management. And Shahar, is something we've been wanting to have in 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 pod, on the, in the helicopter, because you changed my life with that. Uh, it was such an amazing, life changing day and event for me and I can't wait to listen to that podcast. So. But, uh, but it was 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.

Speaker A: Uh, anyways, how do you get the microphone? Is it just a really good, like, noise?

Speaker B: Oh, yeah, yeah. It's canceling. And then the cool thing is that I had a helicopter lesson afterwards, and I'm like, how the heck can. Like, Like. Like, you have to think and not think about this stuff. And, like, how the heck is he doing this? And, like, having this conversation? But anyways, um.

Speaker A: But, yeah, anyways, have you ever, um, seen the, uh. I forget if it's a podcast or if it's just video clips. Uh, the subway takes, uh, that guy Kareem, 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. Who knows about Kareem 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.

Speaker B: Looking at your heart's now, uh, uh, commenting. He says, my friend is a director in big tech company. He told me, shahar, I built AI, uh, agents that ask my team for status updates on their project so they don't forget to send it. And then he said. I said, you realize that your team has agents responding to your agents, and nobody knows what's actually happening, Right?

Speaker A: Do you know what that's called? It's called fabric.

Speaker B: Thank you, my friend. Jar. Really excited. Thank you for changing my life that day. Um. All right. What. Okay. Anything else? Or we're just now rambling here.

Speaker A: What else did we forget? Anything? Any other major topics we should. We should call out to?

Speaker B: All right, well, folks, listening just. I mean, here's another thing for those who are listening. We've been doing this for six years, and people ask us, like, why? Actually in January, I was with, uh, with, uh, 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, yeah, I've actually told

Speaker A: 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?

Speaker B: Well, exactly. It's. I'm like, uh, I wonder about this. And I'm like, I don't know. We just have fun. And this is not, uh. I Mean, this is, I mean, we have no, we keep it super simple and keep it.

Speaker A: There's always more cocktails and there's always more stuff to talk about, right?

Speaker B: Yeah. So I, I wonder what 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, or, or, or have two guests the same time. Yeah.

Speaker A: Can we change the format maybe a little bit and mix it up a little bit?

Speaker B: Yeah. So folks, have any comments, thoughts about that stuff, please. Um, and also, if you want to be on the podcast, let us know. We get a lot of requests and folks listening. I'm sorry, for some people, it's like a lot of PR firms like, oh, you should have this person. Like, 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, you've been listening for a while. If you have, if you really want to be part, just reach out to us. Uh, 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 who's listening. I know there's, there's a handful people who are listening, watching us live right now. You are all amazing. Like, I, I mean, I, I, I, I speak for myself. I'm sure for you too, Tim. Tim is like, we are super freaking lucky to, to have to, to. You've, 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 at conferences and people, like, look at you and want to take a picture with you. Like, that's super cool.

Speaker A: Well, it's hard to believe that, you know, this all started with just turning on Zoom and, uh, and, and hanging out with some friends during a pandemic. Yeah, well, that part was a little

Speaker B: unique, but I guess. Thank you. Pandemic.

Speaker A: Yeah. Uh, Juan, you got any good plans for this summer?

Speaker B: Uh, more travel?

Speaker A: Yeah. Snowflake Databricks.

Speaker B: So June. Uh, all right, just quick June, I'll be, I'll be in Snowflake Summit, and that'll be a Data bricks. And then I'll be in Guadalajara. Mexico. So that's, that's June. Uh, something will happen in July, something August. I'll plan to be a big data London in September. Um, yeah. So things will happen, but, uh, and I will, I will take time off and just be with Disconnect. So we also need to figure out when we're going to start restart the podcast. We'll probably do some rant sessions in the middle. In the, in the.

Speaker A: Yeah, we'll keep, we'll keep it, keep it fresh, keep it exciting. Um, yeah, you know, for me, I, I have a little less travel this summer. Usually I'm, I'm road warring, uh, with you too, but I'm traveling a little less this summer and I'm actually focused on trying to move into my new house. Uh, 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.

Speaker B: All right. Tim is six years, uh, which is. And I think that means that we've officially been working for almost 7.

Speaker A: Mhm.

Speaker B: It has been a pleasure to, to do this with you and I think it, it's, it's just a natural thing. I expected, I expected us to do this every week, uh, and everybody listening. So thank you, thank you, thank you to everybody listening to all our amazing guests and to you, my friend. Cheers.

Speaker A: Yes, Cheers, Juan. And cheers everyone. Have a great summer. Cheers time.

Speaker B: We'll, we'll still be around, we'll be, follow us on LinkedIn, see us at conferences and we'll be doing some brand sessions.

Speaker A: Let's keep the conversation going.

Speaker B: Cheers.

Speaker A: Cheers.