Thank you, guys, for joining us today. My name is Erik Woodring. I lead the hardware coverage here at Morgan Stanley. I am delighted to be joined by Claire Bramley, CFO at Teradata. Claire joined Teradata as CFO in 2021, brings a host of experience from other technology companies, mainly HPQ. You've obviously helped over the last three years, kind of change the dynamics behind the business, cloud-first, focus on execution, financial linearity. So we'll get all into this. So first, thank you for joining. Thank you. Second, let me just quickly go through the normal disclosures. Before we begin, let me point you to Morgan Stanley's research disclosure website at www.morganstanley.com/researchdisclosures. If you have any q uestions, please reach out to your Morgan Stanley sales representative. So, again, Claire, thank you for joining us. Great to see you. Or let's maybe start by talking about the journey that Teradata has been on over the last 3-4 years. What would you say are the biggest changes that you, Steve, and the rest of the team have not only kind of implemented but tried to push forward? And then we'll just take it from there. Yeah. Thank you. Pleasure to be here. Great question, and a lot's been happening at Teradata, as you say, over the last 3-4 years. So when Steve came in, just, you know, 3.5 years ago, completely changed the strategy to make it cloud-first. And I think one of the things that he drove from the very beginning was the focus on technology. So, it was clear that we were behind in terms of the move to the cloud. We were known, very well known and well-respected on-premise for our technology, for our performance at scale, et cetera, but we didn't have a cloud product that was well known about and that had been heavily invested in. And we did have a cloud product, we just hadn't been making investments in it and talking to our customers about it. So one of the first things that Steve did to come in was really focus, you know, the R&D investment into our cloud products. Mm-hmm. And since then, we've had a number of different new product introductions. I think that's one of the biggest differences between Teradata today versus, like, four years ago, is really that focus on innovation. We've seen our VantageCloud Enterprise across all three cloud service providers be launched and go general availability. We have VantageCloud Lake, which is our cloud-native product, and that is now on general availability in AWS and Azure, and coming soon in Google. We have in private preview some great products with regards to ask.ai, AI Unlimited. I can talk a little bit about that later. Oh, yeah. Okay. But there's some [gowrie]. Just this focus on innovation, and I think that's the feedback we also get from our customers, as we've been sharing this with them over the past couple of years, is they've seen more innovation come out of Teradata in the last couple of years than they've seen for the last 10 or 15 years. And I think that's the difference, and that's really been driven by Steve, by our Chief Product Officer, Hillary Ashton, and has fundamentally changed the things that we're driving at Teradata. Now, in addition to that and to support that, we've also been focused very much on our go-to-market. Mm-hmm. and you know, we were very known for kind of direct selling, very good, industry expertise. So Steve made sure that, you know, with our CRO, Todd Cione, that we've set up, you know, clear focus on where we can bring value, make sure that we've got the capabilities to sell cloud, bring, solutions to our customer, and be very much having at the table, having conversations about their long-term strategy and how we bring value, rather than just kind of coming up every three years for a new renewal or something like that. And some of the other big changes in the go-to-market, we were very much not focused on partner selling- Mm-hmm ... and relationships with partners. A lot of the SIs saw as a competitor because we had a big consulting business historically, and so that's something else as well. We pulled back from that consulting focus just to focus on Teradata-specific value-add consulting. And now that means we're able to partner with the Accentures, the Deloittes. We partner very well with the three CSPs. And it's not just, it's co-selling, it's co-engineering, co-marketing, and we also have some good, you know, partners on-prem as well, so with Dell, for example. So I think that, in terms of a go-to-market approach, has significantly changed in the last 3-4 years as we've come in. And then I think the final thing I would add, to your point, about how we execute, and overall execution excellence, just making sure that we've got, you know, day-to-day touch base with our customers, that we have a really good kind of customer health, customer support, team set in place. We have a Chief Customer Officer that, you know, that obviously is his job day in, day out, and he came in with a lot of experience and kind of fundamentally changed, you know, that relationship that we have with our customers on an ongoing basis. So lots of changes. Mm-hmm ... you know, of where we are today, compared to where we were four years ago. Good. So that's a great place to start. We'll dive into all of that, obviously. Let's start kind of nip it in the bud first, which was earnings a handful of weeks ago. You know, you had talked about kind of these two large on-prem erosions that would be a headwind to ARR in 1Q. You know, I just want to kind of give you the opportunity to talk through how long you'd known about those erosions. Were they competitive deal losses? What gives you the confidence that those are isolated, and you're kind of moving beyond that? And then again, we'll kind of continue on the question. Sure. No, absolutely. So, I'm actually gonna take your question and split it into two. Great. So, first of all, just a reminder what I said at earnings, to your point, in Q1, we're anticipating a 4-5 point- Mm-hmm sequential decline, so, compared to where we exited in Q4. So just to kind of put that into numbers- Right ... if you take the midpoint of that, of that number, it's an approximate $70 million sequential decline to total ARR. However, within that, we are planning to grow our cloud ARR sequentially. Yep. So, we do anticipate to see cloud growth sequentially. However, I would point people to, in terms of the size of what we expect that growth to be in Q1 for cloud in dollars, more to be in line with what we saw in Q1 of 2022. Mm-hmm. As opposed to last year, where we had a very large deal that closed. And just to be specific on that as well, that's kind of mid-single-digit dollar growth, sequentially- Okay ... on our cloud ARR. So just to your point, to reinforce some of the linearity that we're seeing, a lot of the, you know, a lot of those headwinds happening on on-prem erosions at the beginning of the year. Mm-hmm. You know, with regards to the timing of those, we've known about the customer intent- Mm-hmm ... to come off of Teradata for a number of years on those kind of two outsized erosions that we saw. I think that was before Steve came on board. Mm-hmm. As you—you know, as I talked about, a lot of progress happening, a lot of new offerings coming to the table in the last three to four years, which didn't exist then. So I think the customers had plans to move to the cloud. We didn't have, you know, a strong product roadmap, didn't have a strong offering before Steve had arrived, and so they had given us the intention to migrate off of Teradata. Now, we've been working with them and many other customers to educate them, to make sure that they understand, you know, what our cloud offerings look like. You know, to—like I said, many customers have been very impressed with the innovation that they've seen over the last few years. And in some cases, Vodafone is a great example of that. We've been unable to get them to stay with us. They were at risk of leaving, had the intent to leave, but then ended up staying with us and moving to the cloud with Teradata. However, for these couple of, I would say, large erosions that we're seeing in Q1, they had already invested heavily in kind of replatforming. And so weren't able to maintain them. However, with one of them, we are talking about potentially working together on new workloads in the future. Okay. So that's a positive sign. Yep. Yep. Yep. So, yeah, so it's something that we've known about for the intent, but the exact timing of being able to predict when they completely move off of us, and in some cases we've been successful at retaining, that's always kind of... That, That, that's the difficult piece to predict. Right. Okay. And then the other side of it, and then we'll get into the exciting stuff, is the cloud ARR deals that you talked about at the end of 4Q into 2024. Again, not competitive losses, but as you guys framed it, you're working with more decision makers at companies, which means things might now take longer than when you were just interacting with IT departments. So you're getting deeper into enterprises, but that also becomes a challenge at some times. And so can you just talk about the visibility into those specific deals that you called out? And you know, based on the conversations that you're having with these customers, you know, why you have confidence they'll close this year, you know, no risk of competition, anything like that? You know, help settle the market when it comes to kind of that debate, so to speak. Absolutely. Yeah, so as you said, we had a handful of deals that slipped out of Q4. We saw the deal cycle time elongate as we're exiting Q4, unfortunately. We were disappointed with the surprise. Mm-hmm. Clearly. It was a surprise to us. A lot of deals closed in the last couple of weeks of the quarter, so we were disappointed not to have seen that earlier in the month of December. However, the good news is, for example, we do have line of sight to be able to close those in the future, and one of them, for example, was already closed, which is good news. Mm-hmm. So of that handful- Good ... of slipped deals, we've already closed one, in Q1, which is good news. And we continue to work, with the customers on the timing. We anticipate to close through the majority through 2024. Naturally, given the surprises that we saw in Q4, we are being conservative and prudent about our assumptions in terms of how long those deals will close. But we, we've taken some learnings from that, tried to ensure that we, are kind of adjusting our processes and our assumptions in terms of, you know, conversion of pipeline, as we look forward. So the confidence that we have, though, as to why these are not competitive effects, is we're still discussing with the customers. We're still talking about what works for them. To your point, some of those are because, you know, decisions are happening, whether it's in the boardroom or at the executive level, because they want to understand their data strategies end to end. Mm-hmm. Other examples, though, one of the larger deals, for example, it was more about M&A corporate development activity. Okay. You know, so just what's the right timing of them to be able to do the deal with us? We're still talking with them. It got delayed because of specific corporate development activity happening at the customer. But it's you know, we continue to work with them and, and confident to close. I think other things as well that, you know, do add complexity with us closing our deals is a couple of our customers are still working on which CSPs they want to use moving forward. Mm-hmm. So again, we can offer across all the CSPs- Yep ... but we need them to make a decision and be clear on the path forward. And so it tends to be a fast follow after that. So lots of different things happening, but definitely, you know, we've factored into our 2024 outlook this kind of deal elongation time, due to your point, a lot of discussions happening, you know, end to end, about data strategies, about AI and how these are executed with our customers, and also at new logos as well. Okay. So, we got that out of the way. Let's talk about product technology, innovation, and all of that. So you mentioned at the top of the conversation, one of the biggest changes since you and Steve came on board is kind of this refocus on innovation and technology. What are the biggest changes you've made? What are the changes you expect to implement, and why does that put Teradata in a better competitive position than you have been historically? Yes. So, I think first of all, one of the biggest changes is just the refocusing of our R&D dollars into the cloud. I mean, the people that know the Teradata history know that we came from a very strong legacy on-prem. And before Steve arrived, we were still investing, you know, 80% of our investment and innovation dollars into on-prem. We made a complete switch, you know, so now 80% is now in the cloud. And what we've seen from that is, you know, VantageCloud Enterprise, as I mentioned, went GA on all three cloud service providers. And then at the beginning of 2023, we launched our VantageCloud Lake offering. Mm-hmm. Now, the way to think about this is, it's a cloud-native offering that takes all the benefits from our on-prem software, so the performance at scale, being able to have the lowest cost per query, having our ClearScape Analytics embedded into the software, being able to, you know, real time in the Lake offering, which is cloud native, the scale up, scale out capabilities. So it kind of brings all of the benefits that you've got in terms of the on-prem. Mm-hmm. But then adding in the benefits that you get for being a cloud-native. Mm-hmm. Obviously, being on-prem, you have, you know, hardware, infrastructure, constraints, capacity constraints. You don't have that in the cloud. I think what we've done is we continue to invest in that offering, though, in the cloud, to enhance our analytical capabilities, to be able to ensure, which is really importa nt with generative AI, the data lineage. Mm-hmm. So really understanding where is your data coming from, what data is being used to get to insights, you know, and having really good visibility of that. That's so important right now in terms of being, having trusted AI and making, you know, insights from AI. Where does that data come from? The other thing as well is what we've embedded into our software as standard is the controls and operations dashboard. So you're able to, even if you've got different departments and functions kind of spinning up local, you know, workloads and new workloads, centrally, you can have good governance. Because that's what we hear from our customers, that they're concerned about the cost, they're concerned about losing control- Mm-hmm ... you know, of people being able to do whatever they, whatever they like in the cloud environment. But we have this dashboard embedded into our software so that you still have, you know, the IT team or the central data team can still have good visibility. So there's a number of things like that that we've been embedded into it. More recently, we have a couple of offerings in private preview with existing customers, and that's what they're excited to see. They're excited to try and pilot some of these new offerings. One of them is AI Unlimited. Mm-hmm. This is a serverless, self-serve, you know, offering of our software, available on AWS, and on Microsoft Azure, and it's embedded. It's gonna be embedded as into Microsoft Fabric- Mm-hmm ... which, you know, very few offerings are planned to be kind of naturally embedded. So that's great to, great to see. And basically, what AI Unlimited enables you to do is be able to use all the benefits of the software without having to set up instances. You can run it serverless, you can run it- you know, you can do very exploratory workloads on it and get using. And I think for new logos or for existing customers that want to, you know, do testing on new workloads, new workloads, and that will go through the marketplace. Mm-hmm. So very easy. You don't have to sign a big contract. You know, it, it's kind of all very much self-serve and serverless, which I think if you think about Teradata from the past, people wouldn't necessarily put those together. Another one I'm super excited about is, ask.ai. Mm-hmm. So this is something that can be used. It's like natural language to be able to help you, to help either write coding, if you're not, you know, if you don't wanna be an expert in terms of to be able to write code, it will tell you how to, how to use, you know, the software, how to get what you want from the software. But the bit that I'm really excited about is the data insights that it can give you. So when you're connected through the software, you can ask it questions about the data that's in there. Mm-hmm. It can give you responses to questions. You know, being a CFO, it's kind of like, tell me. You know, having access to tell me you know, tell me what's happening in this geography. Tell me what's happening in this industry. Tell me what's happening, you know, you know, potentially a, you know, product area. And it gives you all of the answers to the questions that you want. And you can also, the idea is for it to provide you graphical views. You know, show me a graphical view, show me, you know, you know, how am I doing in this particular product, or how am I doing in this particular geography type thing? All in natural language, and so that's kind of really exciting because that just makes it really easy for people to, to use the software, to get insights for the software, and you don't have to be an engineer or a data scientist to get the value from it. I think Hillary would be very happy with that answer. Oh, yeah. You answered about four of the questions that I had for you. Oh, did I? Sorry about that. No, but let's double-click on each of them. Just starting with VantageCloud Lake, because that is kind of one of the newer offerings that you guys have had. Can you just talk about the ramp of that product so far? Sure ... and kind of the customer orientation, whether that's for new customers or existing customers or both, and kind of the materiality of that? Yeah, absolutely. So, just to put into context, as I mentioned, we've had VantageCloud Lake in GA on AWS for 12 months, approximately 6 months for Fabric. So it's still a fairly new- Yep ... product, so it's not a big contribution to our overall cloud growth in 2023. It will pick up as we move out to 2024 in terms of that increased mix. And I think ultimately, Enterprise and Lake will come together—you know, so all of our customers will end up on our Lake cloud native product. Yep. You know, that's something that we can manage for them. We can migrate from Enterprise to Lake very seamlessly. We will, we will work with customers that want to do that. Okay. So, Lake will continue to be the, you know, our focus area of the future, will continue to be the area, the product that we're investing in. We'll still support, obviously, everything on Enterprise, as we've got customers there, but over time, everything will move over, over the next few years to Lake. Okay. Which kind of makes sense for us from a product support standpoint, from an innovation standpoint, having, you know, kind of one best-in-class, leading industry product that you can put all of your industry—you know, R&D focus on. Mm-hmm. And it's, you know, obviously very much simpler for the customer experience as well. Okay. Okay, and then on AI Unlimited, you talked a lot about that, and again, that's even newer, obviously— Yeah than kind of a preview right now. Then kind of preview. Maybe my questions are: what kind of customer is that for? And what kind of competitive advantage does AI Unlimited give you that you didn't have before? Yeah, I think, the ease of use is a big feedback that we've had from Teradata in the past, and I think because this is self-serve, that's a big, a competitive advantage for us, that potentially we were lagging in the past, and we're closing that gap with regards to, competitive advantage. I think the other area that we potentially, have had a, I would say, a bad reputation for is the cost, like the setup cost- Yeah. the initiation cost, and both VantageCloud Lake and specifically AI Unlimited enables people to start with a very low cost. So I think those are really good things in terms of us catching up from a competitive advantage, and being able, being on equal grounds moving forward. To your point about the type of customers, so I think it's, it works both for new logos, because obviously, it's very... It's low cost, it's very easy, it's self-serve, and so new logos can come in and try and see the benefits, you know, of the solution. So I think it's gonna be very attractive for new logos, and they do tend to start small and then build over time. Mm-hmm. Starting small with, you know, something through the marketplace, I think could be very helpful. But I wouldn't disregard the benefit also to existing customers- Mm-hmm because as they're, they wanna do, you know, exploratory type activities within their own environment, it enables them to do that without making a big commitment, you know, in terms of future capacity or, you know, future compute. So I think both from an existing, you know, customer standpoint, where they're looking at new workloads and want to do experimental, exploratory type queries, and for new logos who want to come in, start small, explore the, you know, explore the software, and then potentially grow over time. Okay. So I think it works for both. Okay. And then, obviously, a topic of this conference last year, a big topic of this conference this year is generative AI. Obviously, Teradata positioning kind of in the center of that broader theme. My question for you is kind of, how has this new environment, that we'd say has really gained a lot of momentum over the last 12+ months, kind of changed the value proposition of your offerings? Can you maybe—and within that, can you maybe touch on some projects that you've worked with customers that have become net accretive to Teradata now because of the focus on this type of technology, and obviously, the value prop that you can add? Yeah, absolutely. So I think, I'll go back to something I said earlier, and the importance of having trusted data- Mm-hmm and trusted AI, and I think that plays really well into it, for Teradata's advantage. You know, because we can give people the control, the visibility, the comfort in terms of they understand, you know, through data lineage, where the data's coming from, what data is being used when it comes to generative AI. And, you know, just being able to trust that data and trust those insights that come through AI. So I think that's really important. And I think, you know, some of the things, there's a couple of examples that we've done with a few customers. We had one retailer, for example, that was kind of connecting information across, you know, whether it's like outside conditions, you know, seasonal district conditions, you know, historical buying patterns of a customer, you know, what's, you know, their supply and what's available, and being able to put that together to make recommendations, you know, you know, in natural language, to be able to say: "This is what we think that you should be buying, and this is why," and, you know, et cetera, and just connecting it all together. So there's been some interesting type examples. I think everybody right now is looking at how can they get a return on investment. Mm-hmm. You know, I think, so I think which comes back to why being able to, in private preview, share with existing customers, you know, new software, new offerings that they can experiment with. Mm-hmm. Because I think everybody is... They want to invest, but they want to know that they're gonna get a return on that investment- Yep sort of thing. So being able to, you know, run pilots, being able to do experimental type workload, I think adds a huge amount of value to our existing customers right now. Because they're still working through, like, they're still working, where does it make sense to invest, to focus on? Because it's great to use generative AI. I mean, it, you know, I think we all benefit from it on a regular basis, but do you really get a return on investment? Yep. You know, and that's what they're, they're exploring. And the fact that Teradata is at the table having these discussions with them and being able to bring different industry expertise and, and kind of solution accelerators to the customers, again, is something that we've not been known for historically, you know, three to four years ago, but now is becoming increasingly evident in our conversations with the customers. Okay. Okay, I want to talk about the competitive environment, and, and I don't want to talk about peers, I want to talk about Teradata. And, and the question is: How have you seen the, the competitive environment evolve? And today, what are the key points of, of differentiation that Teradata offers that perhaps others, and even those that are cloud native, can offer? And I know historically we've talked a lot about cost per query. Mm-hmm. Is that still kind of how you would lead that conversation, or has it broadened over time? Yeah, I put it into two main areas. To your point, there is a cost and efficiency element, so the performance. Mm-hmm. I mean, with the customers that we're talking about, global 10,000 customers, they have a huge amount of data. So when you're running their mission-critical operations, they have to run efficiently. Otherwise, you're just, it's just gonna cost you a lot of money. So having really efficient and, and great performance at scale- Mm-hmm ... is really important. And to your point, the cost per query also comes into play. So I think there definitely is an efficiency, performance, cost element. I think the other area that, especially in the last couple of years, that I would say is a, you know, a competitive advantage for us, is the analytical capabilities that are embedded into our software. The amount of AI and ML that's already in ClearScape Analytics, for example, that our customers can use, I think we're at the point it's like customers are, you know, almost struggling to keep up with, you know, with all of the offerings and being able to use it. And so we're working with our customers to get the full benefit out of the analytical capabilities that are already embedded into our software. Right. And I think that's one of the things that we're working with them, and it's clearly an advantage. And I think many customers of us are getting the benefit of that today, but I think there's more opportunity. I mean, I'm meeting with, you know, some of our customers, and especially obviously CFOs peer to peer, you know. And when they say, "Well, I've got this information here and this information here, this information there," I'm like: "You do realize that you can actually use our software to connect this all together, and be able to, you know, to help you with your cash flow forecasting or with your, you know, your long-term planning, and use AI and ML to do that. I think because maybe historically, you know, it's been run by IT, sort of thing, you know, that those advantages, not all of our customers have those full advantages. So that, that's, I mean, that's opportunity for expansion within existing customers, just using the analytical capabilities that already exist. And I'm gonna ask a fairly similar question, but a different way, and that was: In September of last year, we were able to spend time in London around Possible- Mm ... your Possible user event. During some of those discussions, we brought up boomerang customers, customers that had been with Teradata, migrated off the platform, and came back. So in kind of similar to the last question, but when you see them come back to Teradata, what's the main reason you hear why they come back to Teradata? Yeah. I think there's been two main trends that we've seen. And because normally they come back because it's not been working sort of thing. So the migration is normally a big issue. You know, people, I mean, I think people underestimate how much data and how mission-critical the data is. Mm-hmm. And so to be able to migrate that off of Teradata can take years- Mm-hmm ... and then some have had very unsuccessful migrations. Mm-hmm. You know, even after investing a lot of money in the replatforming and managing the migration, they have then struggled for it to then work effectively. So I think migration issues off of Teradata have definitely, you know, paused people. The amount of money that they're spending, how much they realize they still need to spend, you know, to be able to be successful, have been like, "Okay, let's stop. Mm, mm-hmm. And then others who have finally got to the migration have then been and then coming back to the cost that we were talking about, have seen their costs explode, because it's fully consumption and it's not as efficient, and doesn't have that kind of performance at scale, and doesn't have the lowest cost per query. The costs can explode. And I think then we've definitely had customers come back and say: We can't afford this- Mm ... moving forward. This is, like, it's out of control. We need to go back. So although Teradata was kind of perceived historically as expensive- Yeah ... I think when you put it into context of the amount of data, the amount of queries that those customers are running, then, you know, versus kind of like a smaller kind of, you know, startup workload, it does appear expensive. But I think people realize that actually running that amount of data, that amount of queries, it, you know, the cost can get out of control if you're not careful. So, so I would say two things, just kind of issues with migrations and exploratory. I think not many have got to the point of really getting the benefits of the analytics- Yeah ... you know, and then come back. So I think they've had issues before they've even got to that point. But what we're seeing now, you know, we talked about on-prem erosions. What we're seeing is that when we educate our customers and they see all of the innovation and the capabilities that we have, they're like: Why would we leave now? Yeah. Which is good, you know. Mm-hmm. Which is a different conversation than we were having 4 years ago when everybody was like, "Well, why would we stay? Right. Now the conversation is, "Why would we leave?" And that's what we're... You know, we've got to—we've still got work to do. We're still educating the market. We, you know, we still have a, I would say, you know, the brand and reputation to, you know, to be changed from legacy Teradata. But definitely with existing customers that take the time to spend with us, learning about the product, learning about what we're doing, it's changing from "why would we leave? Right. Okay. Right. Okay. Which is great. Perfect. And, and then the last kind of qualitative comment, or question I'll ask before we get into the numbers, is the new logo engine. Yeah. Obviously, we've talked a lot about that, and, and, and you've made changes both to kind of the incentivization of the sales force to push new logos. But how do we think about kind of the timeline for new logos to become, you know, more material to the business? Are there any more changes that you need to implement to kind of ramp that? Let's go from there, and then we'll- Yeah, absolutely. So this is something that we started looking at a couple of years ago, and we know that our future growth, we need to drive new logos. Mm-hmm. I mean, yes, we've got great expansion with existing customers, both in the cloud and on-prem. We see good expansion still on-prem with our existing customers. However, we know that new logos are important. So we did, to your point, make sure that we have the right sales profile to be able to drive new logos. I think one of the things that we didn't really have the product for new logos until 2023. The Cloud Lake product is the best product for new logos, and so that wasn't available until 2023. 2023 as a year for driving new logos from a macro standpoint is probably not the best year. Right. Right. So I would say, we've seen new logos, absolutely. Our pipeline of new logos in Q4 is the highest it's ever been, so that's exciting. Mm-hmm. You know, as we exited Q4. So that pipeline of new logos is increasing. But to your point about, is it a, you know, is it a significant impact right now to our growth? Not yet. But I do see that opportunity with that pipeline, with that pipeline conversion, with the availability now that, you know, we've got VantageCloud Lake and other offerings that are gonna make it easier for new logos to start with us. I anticipate that to increase each year- Okay. in terms of its contribution. Okay. And then, obviously, you've got the expansion that comes with that as well over time. Okay. So, I think it will start to become... "2024, we're still being fairly conservative- Mm-hmm around my assumptions, but as we look out, beyond that, it will become a more increasing benefit to us. Okay. Then let's also talk about kind of the legacy on-premise business, because I think at earnings, you said 70%-75% of your customers have hybrid instances. So it's not like the on-premise business goes away, right? And I think that's a concern with some in the market. But can you, again, a lot of your customers are either well-regulated, which means they have to have an on-premise environment. Can you talk about maybe the steps to stabilization of that business? Because obviously you're also doing some migrations to the cloud, which is still net beneficial, so just a lot of moving pieces. Yeah. How do we think about that on-premise business? Yeah ... more than just 2024, kind of? Yeah, absolutely. So what we've seen, actually, for the last three years, and was assumed in our long, long-range plan modeling, is that if you adjust for conversion- Mm-hmm ... that the expansion on-prem is bigger than the on-prem erosion. Right. Okay. So, you are growing. Net growth. Yeah, net growth, if you adjust for the migration impact. Mm-hmm. We've seen that for the last three years. We have an elevated level, as we talked about, which we see as an anomaly in 2024, just because of the timing of these couple of large areas. But if you look over the long range, you know, period, that still is—you know, that is still accurate. Mm-hmm. It's what we said at our Investor Day back in 2021, and, and that's my anticipation also, as you look at 2025, and beyond. But you- we'll see... We've always said that, you know, adjusting for migrations, you will see, you know, flat to, to low single digit growth, which is in line with the market. Right. That still is still true today. Okay. And hopefully gives people some confidence that, yes, although there's an ongoing level of erosion, that will be more than offset with expansions on-premise. Right. Okay. So, let's talk about... It took us 34 minutes to get to cloud ARR, so let's talk about cloud ARR. That's all right. Obviously, a very impressive journey that you guys have been from effectively having zero cloud ARR to be where you are today. This is a business that's growing, let's call it mid- to high-30%, low-40% expected in constant currency in 2024. So, maybe one question is, just talk about the momentum behind that business. And then two, obviously, you've laid out a goal of $1 billion in 2025. It does mean, you know, 2025, you need some juice behind that business. What gives you the confidence that this business momentum can really sustain beyond 2024 into 2025 to hit that target? Yeah, absolutely. To your point, it's been a great journey. I mean, we finished 2023, even despite the slip deals, you know, at $528 million. You know, over $500 million, half a billion dollars, from nothing- Yeah ... you know, in the last four years, so which is a great journey. The assumptions to get to the midpoint of the outlook that I gave assume that, you know, we continue to see a net expansion rate of approximately 120%. We exit Q4 2023 at 124. Mm-hmm. So a little bit of conservatism in there as I look at my 2024 outlook, but assuming a net expansion rate of approximately 120%, if you apply that on, on, you know, the existing customer base, what you then have to do in terms of migrations and then, uplift at the point of migration- Yeah and then a small contribution from new logos. Mm-hmm ... is not unreasonable to get to the midpoint of the 38%, you know, guide that we gave for 2024. It's the same assumption. If you then assume the same again, approximately the 120% net expansion rate on the 2024 base, and then some migrations and the uplift that we see at the point of migrations and a little bit more for new logos, that's how you get to $1 billion. Right. So, I'm not using any assumptions that we haven't seen in the past. Mm-hmm -and seen to get to where we are today. And actually, I'm being on the more conservative side when I look at my kind of net expansion rate and migrations and uplift expansion. Can you just remind us that point of migration where you go from on-prem to cloud, and there's an expansion? Is Is there a way to quantify that? How do we think about that? Yeah. I mean, originally, when we set our long-range plan, we assumed a dollar for dollar. Mm-hmm. So we didn't assume an uplift, but what we've seen over the past couple of years is, I would say, an uplift that's similar to our net expansion rate. Okay. So that, you know. Yeah, exactly. Yeah. Yeah. So you see that uplift, and it does vary customer to customer. Sometimes it's much higher than that, sometimes it's not, but that is a reasonable assumption to make. Okay. So let's go further down the income statement and talk about gross margins. Again, a lot of moving pieces under the hood because there's a ramping cloud business, whereas you gain scale, you do get better margins, but that is coming off of some products that were also high margin. And so how do we think about the point at which we can see, again, a lot of moving pieces on the top line, but that gross- Mm Margin rate start to re-accelerate? What do you—what are the underlying pieces you need to get there? Yeah, absolutely. So I mean, the main, main driver of our movement in our margin rate is the mix shift. Mm-hmm. You know, mix shift to the cloud. To your point, in 2024, I did outlook that there'll be a gross margin reduction of approximately 100 basis points year-over-year. In 2025, that's when I am expecting the gross margin to stabilize- Mm-hmm So to stop that kind of decline, because with every quarter, with every year, my gross margin on cloud is expanding. Yep. So I expect, you know, the total gross margin to stabilize in 2025, and then start to expand and accelerate in 2026 and beyond. Okay, perfect. And then, last quarter, you also talked about some optimization efforts. Obviously, you know, you're able to drive flash operating margins despite the contraction in gross margins because you're taking some of these actions. What are these actions? Are they structural? Are they just kind of, like, near-term opportunistic? Should that be able to benefit the model beyond just this year as well? How do we think about that? Yeah. So, some of them, to your point, are structural. So like real estate, I've been, this has been my mantra since I arrived. Because now we have a flexible working model, so nobody goes into the office because nobody has to go into the office and we have millions of dollars of infrastructure out there in terms of real estate. So, I've been on this journey, and it takes a few years to move through, you know, a complete, you know, restructure of your real estate portfolio. So that's one that is structural. Once you take that cost away, once you reduce it... So we're not getting rid of all offices, but we're reducing the capacity that we have in our offices, which means that the cost continues to come down. Mm-hmm. You know, and that's the structural benefits, you know? So we're doing things like that. You know, we're implementing a new ERP system. So, you know, things like that in terms of, you know, operational, back-end efficiencies that should come from those investments are structural savings that we should see over time. So they're the things that we're trying to focus on, to your point. It's like, yes, you know, you can always, reduce travel and things like that, you know, you know, on a short-term basis, but I think it's more important to look at what the longer-term structural opportunities are as we move forward. How does everything that we've talked about, whether it's the top line stuff, margins, cost optimization, really translate into, like, cash generation, right? This is a company that is known as having a decent amount of cash generation. As we think about the goals that you set going forward, what do we need to see to get ultimately to where you want this business to be from a cash generation perspective? Yeah. So from a cash standpoint, I mean, the opportunity—we'll start to see the revenue in growth- Mm-hmm Continue to get bigger because of the cloud mix. Yeah. You know, so that will be good. So we'll get, obviously, a benefit from the revenue growth. As I mentioned, the margin and operating income rate will continue to expand as we look out, so that also helps us from a profitability standpoint. And then the other main thing is our working, you know, cash conversion cycle and our assumptions there. We've been fairly, we've been very good at managing our cash conversion cycle. I still think there's efficiency opportunities to improve that. Always. Exactly. Always. So there's an opportunity there, and I think, you know, as we look out to 2024 and 2025 and beyond, there's opportunity for us to get some benefit from our cash conversion cycle as well. Cool. So we could sit here forever. I just want to give you the last word in terms of, you know, what's the final message that you want everyone to take away, kind of, from this presentation and the story about Teradata going forward? I think it's been a great transformation. Transformations are not linear, and I think it's really important to know that the innovation that's happening at Teradata and the relationship that we have with existing customers and the opportunity with new logos is very real. If you look at where we are from a price standpoint right now, it should be a very attractive option. Beautiful. All the best. Thank you so much. Thank you very much, Claire. Cheers. Awesome. Thank you.