If you have any questions, please reach out to your Morgan Stanley sales representative, so thank you for joining us this morning. I'm delighted to be joined by Steve McMillan, CEO of Teradata. Steve is a recurring guest here at the TMT conference. Just so everyone knows Steve's background, spent a number of years within the tech world. Has been at F5, been at Oracle, been at IBM. He kind of joined Teradata to help build acceleration in this transformation. A lot of what we talk about, we'll maybe get to that. So Steve, just thank you for joining us today. Thanks. Great to be here. So, yeah, maybe let's start with exactly what I said, which is maybe helping to elaborate on where Teradata is on its journey to kind of reinvent itself. When I started covering this company a decade ago, it was effectively a fully on-prem hardware business. Prior to your arrival, there was kind of a big push to go cloud native. Now the message is hybrid. So maybe just help us better understand where you are in this kind of evolution and transformation of the company. Yeah, I think hybrid and AI are really foundations of what we're positioning with our customers as Teradata 3.0. When I joined Teradata, we embarked on a course, Teradata 1.0, of becoming cloud first. We pivoted a lot of the company towards cloud. We've reinvigorated our investments in engineering and innovation, pivoted our sales force, built customer success motions. That enabled us to enter into Teradata 2.0, where we really accelerated our progress from a cloud perspective. You know, now we're over $600 million of ARR in the cloud. Well over a third of our business is in the cloud. So we had some real success in terms of moving from that on-prem perception to be seen truly as a capability that can be deployed both on-prem and in the cloud. Now we're into Teradata 3.0, which is, you know, how are we positioning ourselves as a trusted hybrid data platform that can serve the world of AI use cases and advanced analytical use cases? So, there's a lot underlying that. I'm gonna kinda follow that up with two high-level questions before we get into the specifics. The first one is just on the market. When you talk about a data platform, there's a lot that underlies what Teradata does. There's data warehousing, data lakes, lake houses, business analytics, etc. Can you maybe just give us a high-level overview about how you think about those markets right now? And then maybe we'll dig into the Teradata side of what you do. Yeah, I think one of the great things in how we approached our technology innovation was to give our customers real choice, so when they wanted to deploy a technology and their data structures in terms of a structured enterprise data warehouse to run some of their mission-critical financial applications or manufacturing applications from a data and analytics perspective at really high performance with some of the biggest data loads in the world, some of the highest performant data structures in the world, that was a deployment choice in terms of enterprise data warehousing that we enabled for our customers. But we also saw the growth of lake. And so we also invested in technologies that enabled our query engine, which is a really differentiated capability from a massively parallel computing architecture, to really query lake data and enable our customers to deploy in a lake methodology. The combination of those two in terms of a lakehouse. We offer our customers the ability to utilize our technology in any of those three deployment. Methods from a data perspective, but also in the cloud and on-prem. When we talk about the cloud, we are clearly available across all three of the CSPs today, showing good growth from a cloud perspective. The interesting thing is, we still probably have certainly more than 50% of our customers that are in the cloud with us are actually still on-prem with us. So they operate in that hybrid environment. And our technology is actually designed so that we can have a query fabric so that customers can actually deploy their data in the cloud or in an on-prem solution and integrate that data together in a very smart way that enables them to do that without moving lots of data around. Right. We call it take the query engine to the data, don't take the data to the query engine. Right. Okay, and that's maybe a good transition to the kinda question about Teradata specific, which is, you know, can you maybe walk us through the core offerings? And I know that's maybe a bit siloed question, but the kinda core offerings most popular in the market for you today. Really, what the new capabilities are that you're bringing to market that kind of ensures that you remained strongly competitively positioned? Yeah. I think one of the key things from a Teradata perspective is focus. So we know that we serve enterprise customers, yeah? So the largest organizations in the world, that's the real focus area for us. Organizations that have to store, process, get value from data at enormous scale is where the Teradata's core technology offering really differentiates. But over the past couple of years, we've actually increased the analytics capabilities of the platform, quite significantly. So a number of years ago, we bought a company called Aster. We've actually taken all of that analytical AI/ML capabilities that organization had and put them in database. And what that enables us to do with our ClearScape, Offering is essentially deliver a set of analytic capabilities at enormous scale, for the largest companies in the world. Combined with that, we have a very open and connected approach, so Teradata will never get into developing the language model. Capability, but we allow organizations to bring any of their models and language models into the Teradata ecosystem to actually get the benefits from either an AI or a GenAI type solution, but inside the Teradata platform. And we're seeing a lot of interest just now in terms of organizations that want to utilize the right language model, and it may be a small language model or a medium-sized language model or a large language model, inside the Teradata environment. So, a lot of interest around that and bring your own model. And then, the core capabilities of the platform in terms of just providing the best query engine to enable our organizations around the world to get the best out of their data. Okay. That's perfect. And I wanna kind of continue on the theme of competitive advantage. You know, something you've hammered home and that we have, as a firm, have hammered home, is the concept of hybrid cloud, multi-cloud. You're gonna have both, in your enterprise. That gives you a competitive advantage over, what would be cloud-native customers, so to speak. But, what other competitive advantages do you believe Teradata has today? What's the competitive moat that you guys have in this market? Yeah, I think we've got a number of competitive moats, all protected by our patent portfolio, actually. So, if we think about it in terms of three dimensions, one is how do we differentiate in this AI world? And so what we found is that our massively parallel architecture is really good at processing vector stores. When you think about the foundations of AI and GenAI solutions, it's based on vectors and the ability to store, process, query vectors at enormous scale. Our massively parallel architecture that we developed on-prem and can deploy on-prem and in the cloud actually enables us to process vectors at enormous scale and at an economic point, which is much better than our competitors. We're starting a conversation with our customers around the economics of inference. If you think about inference being the underlying capability for AI and GenAI, we can deliver a very economical solution for our customers in terms of that inference capability. A good example of that is we've been working with a number of banks around the world about deploying Hugging Face, a small language model, running inside the Teradata environment, to do complaints analytics, analyzing complaints and then generating next best action in terms of the business process around customer management, and that's enabled us to really focus on what's our differentiated capability from an AI perspective. The next area of focusing for the company is AI on-prem. So there's a lot of deployment in terms of AI solutions in the cloud, but what we've found is when they get to production or enterprise scale in terms of deployment, they become very expensive to run. And so we have a number of customers now that are thinking about if their data gravity. They've got a lot of data on-prem. They've got a lot of processing capability on-prem. We're actually able to deliver an integrated solution, either using third-party language models, but we're also working with Nvidia. In terms of a complete AI on-prem capability that's gonna be available generally in the end of Q2 this year. So that AI on-prem is a second area of competitive differentiation that we're focusing on. And then the third area really is about taking use cases that we've deployed with some of the largest organizations in the world and helping deploy those to other customers throughout the world. So taking financial services use cases around risk, fraud, taking use cases around CX, and managing customer relationships, and then replicating those solutions with customers that can take advantage of the Teradata technology set. So those three areas are the areas of focus for us in terms of how we plan to grow the business as we go through this year. Okay. Something you mentioned, which dovetails into my next question, which is just this partnership with Nvidia. Can you maybe just expand? So it comes out in 2Q. You know, what exactly is this partnership that you've kind of introduced or yet to launch? Yeah, it was great at the most recent Nvidia conference. Teradata was up behind Jensen as he was talking about, you know, strategic data platforms that are integrating with the Nvidia environment. And Teradata is certainly one of those. But that level of tight integration has been recognized by Nvidia in terms of our Enterprise Vector Store capability. So they, as we did a technology briefing, this isn't just a marketing partnership with Nvidia. This is a technology partnership and technology development partnership where Nvidia are looking at the technology that Teradata has in terms of operating vector stores and vector analysis at enormous scale. And they saw the Teradata capability as something that was unique in the marketplace. By taking the Nvidia both hardware stack but also software stack in terms of their NIM capability, integrating that with Teradata technology either in the cloud or on-prem, we are able to essentially offer a full set of AI services for customers that can be deployed in a consistent way across both cloud and on-prem. Okay. Okay. Let's, I think that's a great start. Let's now kind of delve into the business. So 2025, you know, there were a number of kind of headwinds that you faced. There was unexpected on-prem erosion, some deal slippage, some large deals that took longer to close. Can you help give us an update? Just kind of where some of those headwinds stand today and almost a reassurance to the market that, you know, this isn't about competitive losses. Some of these are related to unique factors that you can kind of claw back, so to speak. Yeah. So yeah, the difference for 2025 compared to 2024 is there's gonna be a material change in terms of our overall retention rates in 2025. That's gonna help us, you know, stabilize our base and have, you know, a foundation to our business that's gonna be a platform for growth as we go through the rest of the year. A material change in terms of improvement to our retention rates is gonna be a key difference in 2025 compared to 2024. The other element as we look at 2025 is we did see customers taking their large deal, what we would consider a large eight-figure deal. We usually do a handful of those deals in the year. Last year, we only did a couple of them. I think that's a fundamental change in terms of how organizations are thinking about whether they deploy on-prem or whether they deploy in the cloud and how much to deploy in the cloud and how much to deploy on-prem. We saw a lot of big deals last year actually turn into some eight-figure deals turning into seven-figure deals, where our customers are thinking about, okay, let's be smart about what we put in the cloud and let's be smart about what we keep on-prem. And the great thing about Teradata is we enable that choice for our customers. So those customers are committing and recommitting to the Teradata technology set, but are changing the pattern from a deployment perspective. And I think that's great for us 'cause it's gonna give us opportunity to both grow in the cloud with these customers. But I think what we're gonna see is a growth in our on-prem business as we go through this year. Okay. Perfect, so maybe let's dovetail into that. There's a lot of moving pieces kind of underneath the Teradata business. There's on-prem expansions, there's on-prem migrations to the cloud, there's cloud expansions, there's new logos. Let's just start high level kind of talking us through these different moving pieces and how you think each one of them maybe impact '25 performance. Yeah. I think they all give us opportunity for growth. So 2025 for us is a year where we're gonna return to ARR growth. And that's gonna be driven by all of the factors that you just mentioned. We're gonna have a balanced performance in terms of growth between migrating on-prem technology and capabilities to the cloud and also expansions of our business both in the cloud and on-prem. We're gonna continue to drive new logos. And when in new logos, we're seeing great success in terms of, some use case deployment. We can talk a lot about the new logos in a minute or two. But at our core, we have a very solid business that enables us to have the capability to continue to grow in the cloud, and also continue to expand on-prem. Perfect. It's almost as if, you know, the question list, maybe let's talk about new logos. No, I know this is a smaller part of your business. It is a key focus area for you guys. I think the realization is it, it'll take longer for those new logos to kind of spin up to become material. But there was also a period of time where this uncertain macro environment made it harder to kind of close and onboard new logos. So just where do we stand with some of these new logos that might be smaller and maybe historically taken more of a cloud-first approach? Yeah, I think the key from a new logo perspective for us is to ensure that we've got some great differentiation. I think that's gonna come back to some of the earlier points in terms of we see real success from a new logo perspective when we sell a use case. And we're seeing some real success from a new logo perspective actually on-prem. So a number of the new logos that we're running are in markets where the cloud might not be as mature or as highly regulated. And so those organizations want to have that on-prem capability. And then I think a new area for focus is around AI and taking to customers that message around Enterprise Vector Store, you know, and competing with organizations that you may not expect, Teradata to compete with organizations like Pinecone. which have a vector store capability just now, but we believe that we have a technology that can deploy at enormous scale compared to that kind of offering, and then we're seeing some great competitive win-backs against IBM or traditional competitors like IBM and Oracle, and that's really driven by the true hybrid nature of our cloud capability, and also the fact that our integration with CSPs like Microsoft and AWS and Google is very advanced, and our customers can take advantage of all of our capabilities on-prem and also deploy exactly the same query engine to get the benefit of that in the cloud. So the next question to me is almost like the key question of everything, which is a persistent bear thesis: sure, you'll have success migrating on-premise workloads to the cloud. But what happens to the rest of that on-premise business? Is that a melting ice cube? Or at least that's the thesis. Help us understand why that's not the case. And obviously, if we normalize for migrations to the cloud, you know, it sounds like what you're saying is this on-premise business can actually grow, which would refute that bear case. Yeah. So let's just dig into that if you could, please. Yeah, and I think some of the messaging that you see from Teradata now is moving much more towards hybrid. To one of the points that you made earlier. And I think that just reflects how organizations are thinking about their data estate, where their data is in the state of their environment, what data they want to have in the cloud, what workloads they want to have in the cloud, and what workloads they want to have on-prem. And I think organizations who may have had a cloud-only approach are now rethinking that in terms of it may be from a scale or a cost perspective, but they're thinking about, you know, how can we smartly deploy workload across these environments. And I think that's a key area of differentiation for Teradata. Because we have the same query engine that operates on-prem as we do in the cloud, enables us to seamlessly provide that environment across both cloud and on-prem for our customers. I think as customers think about that balance, we see them thinking about, okay, what are we gonna deploy on-prem? And so one of the banks that we've been talking about actually, when they deployed Hugging Face, they deployed it on-prem. Inside the Teradata environment, and our massively parallel architecture actually enabled them to run Hugging Face in an Intel on an Intel CPU architecture, just as efficiently, more efficiently, in fact, than running it on an Nvidia GPU. Okay. And so, actually, giving our customers that choice of how they deploy these solutions, is a real opportunity for us in terms of future growth. Right. Right. And so it feels like you're completely refuting that in real time, which is maybe when the world thought everything was cloud-only, cloud-native, cloud-everything, but that's not the world today. Yeah, I think that as just the statistic, there's, you know, over 50% of the customers that are with us in the cloud are also on-prem. Right. Hybrid is the world today, and we are uniquely placed to serve that marketplace. Okay. Perfect. You know, you mentioned two questions ago, some customers that I guess I call them kind of boomerang customers. They were once with Teradata. They went off the platform. Now they've come back. Why are they coming back? How common is that? Is that becoming increasingly more common? Can you just add some context to that? Yeah, I think, there's no better ratification of our strategy when a, a customer chooses to, come back to the Teradata and utilize the Teradata technology set. And that's certainly one of the new logo motions that we have. Yeah. And we do see that. And usually it's driven by customers recognizing the, the beneficial economics of utilizing the Teradata platform for their at-scale enterprise-wide workloads. Because we are very efficient, very effective in terms of delivering those workloads at a competitive price point for our customers, in some cases an order of magnitude cheaper. But some of the new capabilities and workload cases that we're seeing just now are actually looking at workloads which would be more associated with Databricks. As an example, so I mentioned about our technology innovation in Teradata 2.0 in terms of building up ClearScape Analytics. That's enabling us to deliver to our customers analytical capabilities that compete with Databricks at enormous scale and at a cost point and a price point that's much less than Databricks utilizing those technologies and for Databricks. And we can do that both on-prem and in the cloud. Perfect. I'm gonna quickly touch on consulting just to kind of get the question out of the way, which is, you know, 15% of your business still has consulting. You know, the results there have been more inconsistent. Just maybe my question is, you know, why still have this business? What does it enable? What do you need to do to kind of get it to stabilize? Yeah. When I first joined Teradata, I said at our core, we were gonna be a technology company. And I think that was really important to set out in terms of, we're not gonna be a consulting and services organization. I think at one point, the consulting revenue streams for Teradata were up over $500 million a year. But as a technology business, you do need a consulting capability to take these value propositions to the market, and take our technology capability to the market and enable our partner focus, in terms of working alongside partners to deliver a complete service to our end customer. And that consulting capability enables us to deploy our technologies in unique and innovative ways. It enables our customers to take advantage of the technologies to solve real business problems inside their environment every single day. And so I think we are. We've been over the last four years right-sizing our consulting business. And I think now it's getting to the point where it's the right size to enable our technology business and enable growth in our technology business. And that's really the focus for our consulting organization. It's not to be a consulting for the sake of consulting. Right. It's consulting to drive our technology and our ARR. Okay. Perfect. I wanna go back to maybe what some of the earlier conversations. You have launched kind of a lot of new offerings and products. So Enterprise Vector Store, a few years ago it was Vantage Cloud lake. The second half of last year, AI Unlimited. Can you talk about the relative areas of kind of success that you've had with these handful of offerings? I'm kind of taking three different technologies but bringing them together into one. Just where is the relative strength coming in? And how does that relative strength inform you where the next leg of innovation comes from? Yeah, I think all of those innovations that you just mentioned have helped Teradata reposition ourselves in the minds of our existing customers, but also our new prospects. So if you just think about it, Vantage Cloud lake was all about saying, "Hey, we're not just an enterprise data warehouse company. You can use our query engine to solve and address all of your lake, all of your unstructured data, and utilize the Teradata technology to process that." The innovations around AI Unlimited enabled us to be natively integrated into Microsoft Fabric. You know, Satya stood up on stage last year, had the big Teradata logo behind them as one of the five ISVs that's natively integrated into Microsoft Fabric. Again, a complete repositioning of Teradata. That technology actually is a serverless query engine. And who four years ago, when you were initially covering this, Eric, who would've thought that Teradata would come out with a serverless query engine given our integration with server technology in the world? So again, it enables us to reposition the Teradata technology stack against a brand new set of use cases, integrated into Microsoft's data fabric. So all of these innovations are kind of building the foundation of a totally flexible data platform that can be deployed in a number of different ways. And then we are building on top of that now our AI capabilities. We just had a press release on Monday, talking about some of our Enterprise Vector Store and AI capabilities, our integration with Nvidia, our AI Workbench capability that will enable customers to deploy AI solutions in a very effective way. At the end of Q2, we're coming out with an AI on-prem offer. which will integrate together in an on-prem packaged offer, NVIDIA capabilities and Teradata technologies, for a distinct solution set for our customers. And then in the third quarter, that enterprise packaging up that entire Enterprise Vector Store to offer an end-to-end management model around vector store for our customers. And if you think about the massive opportunity there is around vectors, as AI starts to vectorize all of this unstructured data, documents, video, sound, they're gonna have to store those vectors. And that's gonna be a huge opportunity for organizations that have a unique capability to store, analyze those vectors at enormous scale. And that's what our offer's gonna enable in the third quarter. Okay. Exciting, and I wanna talk about Cloud ARR, because it obviously has been a massive growth engine for you guys. You know, you're guiding to 14%-18% constant currency growth this year. But what I hear from you guys is more kind of confidence in the back half of the year and actually, you know, the chance for this business to accelerate through the year. So, one, where does the confidence come from? Two, you know, would you say maybe you have more, I guess, improved visibility into this business than maybe you did a year ago? Yeah. What gets you excited about that second half? Yeah, I think 2024 was a year where we changed some of the fundamentals of our execution. We brought in a new chief revenue officer. We restructured our sales organization from a worldwide perspective. We put new leadership into our sales organization, both in terms of our new logo engine, but also in terms of globalizing some of our industries like financial services, which has really enabled us to take value propositions that we're deploying in Europe, bring it to the Americas, things that we're doing in the Americas, taking it to APJ, and delivering a really focused set of offerings for those institutions. But as we've invested in our go-to-market operations, it has enabled us to get better insight into the deals that we're doing. Certainly we are not looking to depend on very, very large eight-figure deals. As we have in the past in terms of execution. And so, as we look at our outlook for 2025, we believe it's very pragmatic. We set a range which we think we can deliver in from a cloud perspective in every single quarter. We are very back-end loaded as an organization. In terms of the interactions that we have with our existing customer base, they tend to be fourth quarter. I nteractions. So that back-end waiting is still there for us. But what we're gonna demonstrate as we go through Q1, Q2, Q3 as a consistent performance and a consistent cascade that gives us confidence in terms of executing in Q4. Okay. That's perfect. Let's talk about the cost side of things. This is a CFO question, but I'm gonna ask you the CEO, which is, you know, there has been a renewed focus over the last six-plus months on kind of cost efficiencies. What actions have you taken? What's kind of the financial impact that we should expect and the timing of that financial impact? Yeah, I think since I joined Teradata, our focus has always been profitable growth. And so making sure that we are prudent with the investments that we're making. We're making targeted investments inside the business and that we continuously look at how we can operate more efficiently, more effectively, to essentially ensure a good shareholder return. And so when we look at our investment envelope, we do that very judiciously in terms of ensuring that we're continuing to drive efficiency and effectiveness, but we're also investing in the right areas of the business for growth. Some of the actions that we took in 2024 were essentially to get the right financial foundation from a cost and expense perspective to deliver that shareholder return in 2025. But we're also making sure that we're investing in the innovation that we have inside Teradata. Maybe to that point, if I think about capital allocation, you're committed to returning more than 50% of free cash flow to shareholders. You know, that is a little bit lower than the target last year, but I do hear you talking about kind of areas of reinvestment. Kind of to continue the growth engine. Help us understand the capital allocation priorities and kind of the intensity of that reinvestment this year. Is it different than past years? Yeah, I think, by taking that return from 75-50, it gives us more. Operating flexibility inside the business. Yeah, and as we look at the balance sheet overall, we believe that that capital allocation will enable us to be more flexible in terms of our operating principle and operational execution for both this year, but also into next year, and so we actually returned. We set a target last year of at least 75% in 2024. We actually returned more than 75%. But we see delivering more than 50% of Free Cash Flow to our shareholders in 2024 as something that's realistic and still gives us the operational flexibility from a balance sheet perspective. Okay. Perfect. You know, I'm gonna look kind of beyond 2025 'cause I realize 2025, there's still a lot of moving pieces, in the quest to get back to growth. You have ARR growth. You know, if we look back, there was once a time, where Teradata had guided to over $450 million of kind of annual run rate free cash flow. You know, is there a path to that type of cash generation in this business? And is there any way that you can help us think about, like, if you had the magic eight ball, kind of timing for that potential? Because, you know, if you look at the stock price, compare it to what the free cash flow potential of this business could be, there could be a material difference in how we might think about things. Yeah, I think, you know, if I look at the current stock price and compare it just to today's free cash flow. Right. Our free cash flow outlook for the year. Yeah. There's certainly opportunity. Right. Right. In terms of from a value perspective and gaining value from the Teradata investment. What I would say is, this year we're returning to ARR growth, which will return us to revenue growth in 2026. And that will enable us to significantly improve our free cash flow position as we go through the subsequent years. That return to growth based on better retention rates, improved cloud mix and growth in the cloud, and a strengthening of our on-prem business will enable that growth and enable us to grow free cash flow into the future. Okay, and maybe that's a good way to end with my last question, and maybe it's repetitive, but I wanna make sure it's hammered home, which is, you know, help us all understand as we sit here with Teradata starting 2025, what's most underappreciated about the story. A lot of moving pieces, a really exciting end market, but what should we all get excited about, and maybe what is the market not understanding or underappreciating? Yeah, I think Teradata 3.0 is all about innovation and an AI world. So we truly believe that we have the trusted hybrid data platform for AI. And that's something that level of innovation that we're delivered to is uniquely set as a part in the marketplace. I think is something that's underappreciated, but our customers are starting to appreciate that right now. Perfect. That's a great way to end. Awesome. Thank you so much, Steve. Thanks, Eric. Thank you.