 Okay, we're here with Suresh Fatal, who's the Chief Product Officer at Altrix, and Adam Wilson, the CEO of Trifacta. Now, of course, a part of Altrix. Just close this quarter. Gentlemen, welcome. Great to be here. Okay, Suresh, let me start with you. In my opening remarks, I talked about Altrix's traditional position serving business analysts and how the Hyperana acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? Yeah, thank you. Thank you for the question. You know, we see a massive opportunity of helping brands democratize the use of analytics across their business. Every knowledge worker, every individual in the company should have access to analytics. It's no longer optional as they navigate their businesses. With that in mind, you know, we know designer and the products that Altrix has been selling the past decade or so do a really great job addressing the business analysts. With Hyperana, now kind of renamed Altrix Auto Insights, we even speak with the business owner, the line of business owner, who's looking for insights that aren't revealed in traditional dashboards and so on. But we see this opportunity of really helping the data engineering teams and IT organizations to also make better use of analytics. And that's where Trifacta comes in for us. Trifacta has the best data engineering cloud in the planet. They have an established track record of working across multiple cloud platforms and helping data engineers do better data pipelining and work better with this massive kind of cloud transformation that's happening in every business. And so Trifacta made so much sense for us. Yeah, thank you for that. I mean, look, you could have built it yourself, would have taken, you know, who knows how long, you know? But so definitely a great time to market move. Adam, I wonder if we could dig into Trifacta some more. I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well on theCUBE. Coming at the problem of taking data from raw refined to an experienced point of view. And Joe in the early days talked about flipping the model and starting with data visualization, something Jeff Heller was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you maybe, and some others, changed that model with EL and then T. Explain how Trifacta really changed the data engineering game. Yeah, that's exactly right, Dave. And it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research at Berkeley and Stanford, that really birthed Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why has this become the exclusive purview, the highly technical? And, you know, can we rethink this and make this a user experience problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So a broader set of users can really see for themselves and help themselves. And I think that there was a lot of pent-up frustration out there because people have been told for, you know, for a decade now to be more data-driven. And then the whole time they're saying, well, then give me the data, you know, in the shape that I can use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and not empower me to get in there and to actually start to work with the data in meaningful ways. And so that was really, you know, what, you know, the origin story of the company. And I think as we saw over the course of the last five, six, seven years that, you know, a real excitement to embrace this idea of trying to think about data engineering differently, trying to democratize the ETL process and to also leverage all these exciting new engines and platforms that are out there that allow for, you know, processing, you know, ever more diverse data sets, ever larger data sets in new and interesting ways. And that's where a lot of the pushdown or the ELT approach is, you know, I think it could really won the day. And that for us was a hallmark of the solution from the very beginning. Yeah, this is a huge point that you're making. This is, first of all, there's a large business is probably about a hundred billion dollar TAM. And the point you're making, look, we've contextualized most of our operational systems, but the big data pipeline hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is nirvana, but it's been historically very difficult. You've got the number of companies, it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altrix as you bring these puzzle pieces together? How is this going to impact your customers? Who would like to take that one? Yeah, maybe I'll take a crack at it and Adam will add on. You know, there hasn't been a single platform for analytics automation in the enterprise, right? People have relied on different products to solve kind of smaller problems across this analytics automation, data transformation domain. And I think uniquely Altrix has that opportunity. We've got 7,000 plus customers who rely on analytics for data management, for analytics, for AI and ML, for transformations, for reporting and visualization, for automated insights and so on. And so by bringing trifecta, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where analytics gets applied and so multiple personas. And now that we just talked about the data engineers, they are really a growing stakeholder in this transformation of data analytics. Yeah, good. Maybe we can stay on this for a minute because you're right, you're bringing together now at least three personas, the business analyst, the end user, slash business user and now the data engineer, which is really Adam and I.T. role in a lot of companies and you've used this term, the data engineering cloud. What is that? How is it going to integrate with or support these other personas? And how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? Yeah, no, that's great. I think for us, we really looked at this and said, we want to build an open and interactive cloud platform for data engineers to collaboratively profile, pipeline and prepare data for analysis and that really meant collaborating with the analysts that were in the line of business. And so this is why, a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision-making and allow for that, what I would describe as collaborative curation of the data together so that you're starting to see increasing returns to scale as this rules out. I just think that is an incredibly powerful combination and frankly something that the market has not cracked the code on yet. And so I think when I sat down with Suresh and with Mark and the team at Altrix, that was really part of the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. Yeah, and you're really, you're obviously riding the cloud and the cloud native wave. But specifically we're seeing, I almost don't even want to call it a data warehouse anyway because when you look at what's for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse. It's simplified, get there fast, don't necessarily have to go through this central organization to share data. But it's really all about simplification, right? Isn't that really what the democratization comes down to? Yeah, it's simplification and collaboration, right? I don't want to kind of just, what Adam said resonates with me deeply. Analytics is one of those massive disciplines inside an enterprise that's really had the weakest tools and weakest of interfaces to collaborate with. And I think truly this was, Aldrich's end of superpower was helping the analysts get more out of their data, get more out of the analytics. Like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, understanding data models better. I think curating those insights, boring Adam's phrase again, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. So how should we think about designer cloud, which is from Aldrich's? It's really been the on-prem or the server or desktop offering and of course, trifecta is about cloud data warehouses, right? How should we think about those two products? Yeah, I think you should think about them and as very complimentary, right? Designer cloud really shares a lot of DNA and heritage with designer desktop, the low-code tooling and the interface that really appeals to the business analysts and gets a lot of the things that they do well. We've also built it with interoperability in mind, right? So if you started building your workflows in designer desktop, you want to share that with designer cloud, we want to make it super easy for you to do that. And I think over time now, we're only a week into this alliance with trifecta. I think we have to get deeper and start to think about what does the data engineer really need, what does the business analysts really need and how do designer cloud and trifecta really support both of those requirements and why can it continue to build on the amazing trifecta cloud platform? I was just gonna say, I think that's one of the things that creates a lot of opportunity as we go forward because ultimately trifecta took a platform, first mentality to everything that we built. So thinking about openness and extensibility and how over time people could build things on top of trifecta that are a variety of analytic tool chain or analytic applications. And so when you think about all tricks now starting to move some of its capabilities or to provide additional capabilities in the cloud, trifecta becomes a platform that can accelerate all of that work and create a cohesive set of cloud-based services that share a common platform and that maintains independence because both companies have been fiercely independent and really giving people choice. So making sure that whether you're picking one cloud platform or another, whether you're running things on the desktop, whether you're running in hybrid environments that no matter what your decision, you're always in a position to be able to get out your data, you're always in a position to be able to cleanse, transform, shape, structure that data and ultimately to deliver the analytics that you need. And so I think in that sense, this again is another reason why the combination fits so well together, giving people the choice and as they think about their analytics strategy and their platform strategy going forward. Yeah, I'll make it chuckle. One of the reasons I always liked all tricks is because it kind of did a little end run on IT. IT can be a blocker sometimes, but that created problems, right? Because organizations said, wow, this big data stuff is taking off, but we need security. We need governance and it's interesting because you got, ETL has been complex, whereas the visualization tools, they really weren't great at governance and security. It took some time there. So that's not their heritage. You're bringing those worlds together and I'm interested, you guys just had your sales kickoff. What was their reaction like? Maybe Suresh, you could start off and maybe Adam, you could bring us home. Yeah, thanks for asking about our sales kickoff. So we met for the first time in kind of two years, right? As it is for many of us. In person, which I think was a real breakthrough as all tricks has been on its transformation journey, we had a trifecta to the party such as it were and getting all of our sales teams and product organizations to meet in person in one location. I thought that was very powerful for us as a company. But then I tell you the reception for trifecta was beyond anything I could have imagined. We were working, Adam and I were working so hard on on the deal and the core hypotheses and so on. And then you step back and you kind of share the vision with the field organization and it blows you away the energy that it creates among our sellers, our partners. I'm sure Adam and his team were mobbed every single day with questions and opportunities to bring them in but Adam maybe you should share. Yeah, no, it was through the roof. I mean, the amount of energy, when certainly how welcoming everybody was, just I think the story makes so much sense together. I think culturally the companies are very aligned and it was a real capstone moment to be able to complete the acquisition and to close and announce at the kickoff event. And I think for us, when we really thought about it and the story that we told was just you have this opportunity to really cater to what the end users care about which is a lot about interactivity and self-service. And at the same time, and that's a lot of the goodness that Altrix has brought through years and years of building a very vibrant community of hundreds of thousands of users. And on the other side, trifactive bringing in this data engineering focus that's really about the governance things that you mentioned and the openness that IT cares deeply about. And all of a sudden now you have a chance to put that together into a complete story where the data engineering cloud and analytics automation come together. And I just think the lights went on for people instantaneously. And this is a story that I think the market is really hungry for. And certainly the reception we got from the broader team at kickoff was a great indication of that. Well, I think the story hangs together really well. One of the better ones I've seen in this space. And you guys coming off a really strong quarter. So congratulations on that. Jens, we have to leave it there. Really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching theCUBE, your leader in enterprise tech coverage.