 Well, thank you for having me out to dbt labs and co less. I'm here Again with Tristan handy and we're having a little discussion about the next set of data Platforms how the modern data stacks can evolve and I think what was neat and hearing you on stage is really how dbt is at the center of that how you're almost becoming that API layer in between Multiple data platforms, so why don't you kind of explore that a little bit and give us a little bit more of a sense on what you're seeing and Kind of the areas around you as well as what you're actually doing Yeah, thanks for being here the I think that We are extremely focused on Interfaces between teams right now I don't know that we're focused on being the API to data platforms, but we are definitely Okay, so so the the ecosystem the data ecosystem last summer was very focused on this conversation around data contracts and a lot of the focus was around the the Division between data producers and data consumers and data producers were generally folks like software engineers who were building applications And then the downstream data consumers were upset that they continue to break Their interfaces change their schemas and will break downstream pipelines. Like how do we prevent that from happening? The API is that we are very focused on that we have a lot of visibility into Are the ones between different data teams? so this is not something that ends up happening inside of you know a Small company that has five people on its data team But you know if you have five people in your data team, you probably all work really closely together you understand everything that's going on inside, but larger organizations have to create Modestly sized teams and they own specific areas of the the data code base, but inevitably Those are not isolated. They have relationships between one another You've got the finance people and the marketing people in the what however you decide to divide up your areas of responsibility and Those interrelationships You can kind of have two ways of dealing with that You can say okay the finance people and the marketing people don't trust each other and so they're going to rebuild everything from scratch Then when they all show up in a meeting together turns out everything disagrees and they get to fight about it Or you can Have them rely on each other's data but Without sophisticated enough tools that means that when the marketing people make some change they break the finance people stuff and so what we are trying to do is create the ability for Large larger teams to Reliably rely on other people's data and Be able to trust it so that they don't have to rebuild it from scratch And so they don't constantly see other teams breaking their stuff And we think about this a lot in the same way that you would think about Two pizza teams service oriented architecture where like you own your own code base And then your responsibility is to expose interfaces to other teams and prove that those Interfaces are not going to break all the time So I think again the two pizza team thing. I mean beyond giving me PTSD from my time at AWS I think is a really good example because a lot of times within Amazon for instance There's a lot of people who the two pizza teams don't talk to the other two pizza teams And I think that's where I think what you guys are doing is really solving for that and Help how you help people because a lot of your core To almost use it, you know quite literally the DBT core user set that huge community There's a ton of people who are out there and they you know again They've gone and I again your DBT CLI coming to cloud I think was huge for that community because I think they're really this is where they live and they They work on a daily basis and now having that is a huge advantage. That's what I want to yeah No, I I'm also excited about that Like I have developed over the years the muscle memory of like typing the DBT commands into the CLI and like that's that's what I want to be doing so I'm very excited about it Yeah, and I think that when you start to look at and pull back to how this starts to bring it together again You you talked about it I think Louise talked about it a little bit and we talk about it a lot is you know The concept of data features and data products and how you start to build that stack up on top of DBT and That now that semantic layer that you guys are putting in there as well and I think to me it Really is starting to put some guardrails in from a semantic and I think it was lightly talked about by Lewis about round The governance aspect of it and how you bring down and say okay Here's where those data con almost data contracts can interface in mesh How is this when you start to look at it? Are you saying to your your community? Hey, if you if you're happy with DBT core, maybe you're a five-person shop You're you're building some models and you're trying to get off the ground stay with DBT core as you start to grow DBT cloud is going to be where you want to operationalize that is that kind of how you see people moving into DBT cloud because you Again, I think you did a great job talking about the sustainability and making the company sustainable and Staying and remaining Apache at the same time for core So is that how your vision where it's hey, we're going to build up the value enough within cloud to really Incentivize you as you grow start here grow to here So I think that they're they're two big stories for for cloud. I think you're basically exactly right The the one that we've been very focused on this year is Making DBT cloud the place to scale your investment with DBT and that That comes in a couple of different ways like with mesh with Explorer It is a realization that your you know large companies DBT investments are very complex And you need solutions to actually be able to to scale with them effectively but it's also the fact that different DBT developers have different Preferences in terms of how they write code how they manage their own development environments and so now DBT cloud being able to address both power users via CLI and Folks who are just getting started with DBT via the IDE in the browser I think that that is a major part of like how Larger organizations scale DBT out to like many many users The other big part of the story that we haven't spent as much time on recently But I want to be able to get back to Is that I think cloud software has an ability to create user experience that open-source software often struggles with and I really It's funny. There's a thing that's happened in the past. I don't know two or three years where DBT has become a tool that is widely used by data engineers And the funny thing about that is that DBT Was originally not developed to be used by data engineers. It's a data engineering tool But it was meant to unlock the power of data engineering to a larger group of people and So I'm I'm don't get me wrong. I'm very very happy that data engineers are using DBT, but I want to also continue to invest in Expanding the set of users who Can realistically use DBT and I think that Usability and like really like removing friction from the process is is key there and I think that clouds a real enabler for that Yeah, I think we see that as well at that a lot of Companies I mean you I mean if you don't mention AI you almost get kicked off the internet these days, right? So I think from using LLMs to do, you know co-pilots and things like that to make it easier Do you see I mean that's Perfect example of where it's very you know, we call it instead of an LLM You know an SLM a segmented or small language model that's very specific to a job be it You know HR be its CFOs organization and finance be it, you know helping code in a particular Application is that where you see the power of this going in the future is something like that to help people Really build their data products and go up the stack Yeah, I I There's a lot of benefits that come from being code first But I wanted to be code first originally because It kind of gave you a lot of stuff for free version control CICD all of this stuff I Didn't anticipate in 2016 that by being code first Meant that it was very easy to integrate new advances in AI into the dbt workflow. So I have This is not a thing that we have Teams of engineers on the ground working on today, but I would be shocked if we didn't in the not too distant future because I think that the combination of the fact that dbt is code first and That has become such a widely used standard Every large language model out there can write dbt code you say You know the prompt that I've used over and over again is I'm a very experienced analytics engineer And I've been using dbt for years I have a data set that looks like this and another one that looks like this Create me a model that joins these two data sets together Then does the following things with them and it freakin writes dbt code for you and it's good So this is this is not the land of science fiction. Like this is a thing that I think is really going to come together So with that and and I think kind of bridging off of your your Keynote again, I think the sustainability of the company you had a great ramp there You had that little slide with the the growth, which was fantastic In fact, it moved too quick that I didn't get a photo of it So so I'll have to get that from you later on but I think it's it's you look at that how the company is growing Just in you know a few minutes that we have left here Why don't you talk about Because I think you were very passionate about how you're building the company and your your vision for the company And it's customers in the community. Why don't you kind of give people a little bit of insight that may have missed Your keynote on that because I think to me that was that was impressive Thanks. Um Yeah, it's It's been it's been such a funny journey the um Fortunately, we are not the first commercial open source company the company that has had to go from a very loyal Following of early open source users To to becoming a real commercial business And and so we have we have playbooks to look at But I think that everyone who goes through this journey gets to like relearn some some things You know many of our early employees were people that we hired out of the dbt community and There is just like this fervor around like the benefits of this community and around the open source and I think that As as we scaled we needed to layer on not replace but layer on like an actual Like capitalist motion like it's it's kind of strange to say because um, you Uh, you expect when you work for a for-profit company that like somewhere somebody has to be making some money but uh The ideals of open source software unless you take very Good care to like weave them into a commercial story They can feel very antithetical to Building a for-profit business and so we've we've kind of in the inside of our own company We have gone through the cultural changes over the past couple of years That we needed to do to to like be ready to go in that next phase of our journey And I think we're doing that in the community as well um We are continuing to invest real resources into dbt core and that's what all of this is built on like None of this would would exist without open source But you'll see that a lot of our innovation right now is happening inside of dbt cloud And a lot of our product announcements are happening inside of dbt cloud and You know it it goes back to that like Who are each of these products for and I think that core is a great way to get started It's a great way for small teams cloud is solving real user experience challenges and it's solving real scale challenges No, I think it is and I think the way that you have approached it having been at an open source company myself And seen it and work we work with a ton in the open source community I think the way that you're approaching it is a I think a good way and I think you know one of the things that I'll give you also kudos on is your transparency about it I think there's people will look at this and and say hey This is how they made that transition because to your point there are playbooks for going and doing it But at the same time I think it's a It's not easy and like you said you it takes time to change that culture internally as well and so Where do you see yourself a year from now? From a dbt perspective and dbt labs perspective in vegas we we uh tried to Uh, we tried to lock this venue. I love this venue. I didn't it doesn't come through in the video But I'm super happy with san diego and by being by the bay and that the hotel's been great the They were booked for next year and so we're we're taking the show to vegas next year. Um, but no the uh I think that over the coming year We are going to have the opportunity to really Iterate on a lot of the things that we put out this year So you've seen us plant some big news stakes in the ground Like this is the first time that we've talked about dbt mesh. It's the first time we've we're launching explorer Which is like a mini dbt data catalog And it's it's the first time we're actually going to start selling the semantic layer It you know a lot more to say on all of these things, but like having these big tent poles out in the universe We now are moving away from this like Let's go into the lab and you know Come out with something great and now these this stuff is in people's hands And we're just in the process of iterating as fast as we can to to continue to develop it Well exciting stuff. I'm really I again, thanks for having me out for this Very excited. Uh, thanks for coming on board tristan. I think it's you know Good stuff and i'm excited to see where you get to in the next year. Thanks a lot Yeah, and thank you for watching the cube. We're the leader in tech analysis and Coverage and keep it right here. We have some more coming from dbt labs coalesce and we'll see you soon