Great. Why don't we go ahead and get started? Look, we're just delighted to have Chris and Hillary from Teradata. Hillary has been there three years as the Chief Product Officer, has a really interesting background, so we'll spend some time getting to know her. Then just to start us off, because I always ask, and I wanna know, Chris, how's business? What would you say? Pat, thanks again for the opportunity to be here with all of you today. Pat, business was great. As you saw from our February call, you know, we had a very strong quarter to finish off the 2022 fiscal year. We're carrying that momentum into 2023. You know, we've had a strong period in light of a pretty turbulent and volatile macro, which we've been relatively resilient to. I think those characteristics are gonna, you know, carry us forward. It's strengthening our pipeline. We're running production mission-critical workload for our customers. We have less volatility because we're not as exposed to consumption pricing. All of these are very strong factors in Teradata's favor, and again, we're gonna look to carry that momentum. Awesome. Okay, Hillary, where are you from? I'm from San Diego now. Like, where were you born? You lived there. Yep, I live there. I moved there for the job. Where are you from originally? Boston. From Boston? Yeah. I'm not gonna go all the way back to the beginning, but you were at SAS for a little over a decade, right? Yep. That's right. 2003- 2014. Yep. What is SAS? Um. This is an interesting company, right? SAS is an interesting company. Yeah. Based out of North Carolina. Founder-owned and operated. Is it Goodnight? Something. Yeah. Jim Goodnight. Is that right? Is that right? Jim Goodnight. Yep. Very analytics focused. They do analytics for some of the largest customers on the planet. It's actually where I first bumped into Teradata. Understanding that what Teradata could do with analytics at scale was absolutely incredible. Totally. Even at that time, kind of best in the market. I don't know the right way to describe. When you were there, how dominant were they in the market, and what was the market they were in? Yeah. SAS was incredibly dominant at the time. Largest financial services telco retail providers on the planet were using SAS for. Mm-hmm. Analytics, and model development, and deploying on, amongst other things, Teradata, to get that at scale. I was really focused on the Customer 360 marketing technology side of the business. That's where I cut my teeth on analytics like, you know, next best offer, next best action, really understanding the analytics and data behind analytic outcomes. Okay. I didn't understand that. It would have run on top of Teradata. That's right. Oh, interesting. Yeah. What else would it run on top of? They had their own proprietary data, environment, but also ran on Oracle, Db2, going back a little bit. Mm-hmm. Yep. AIX. Okay. We roll around to 2014. Mm-hmm. And what do you thinking, how come? Yeah. You decide to leave? Yeah. Yeah, sure. I'll just walk through. I won't make it super painful for you. Joined a startup based in Bangalore, India. Really focused on retail analytics, prepackaged retail analytics. Saw a huge opportunity in the market. Analytics is hard. It requires large teams of data scientists. Retail is traditionally less well-funded compared to banks' ability to do that. Joined a company based out of Bangalore. Led their America's operations, including product, but largely focused on go-to-market opportunities there, to really take prepackaged analytics across customer journey and also merchandise assortment to the Americas market f rom there. What does that mean, merchandise assortment? Retailers do assortment planning. If you're a Target or a grocery chain, you wanna figure out what should I have on hand, how many red scarves should I have on hand during Christmas time, that kind of thing. It's a little bit more complicated than that, but it's, you do some analytics to be able to understand what you should have in a particular store based on who shops that store. Mm-hmm. Seasonality and, local trends. Mm. On the soft goods market, which would be the clothing market. Mm-hmm. There's hard goods like grocery. Is it the same as demand planning? It is. It's assortment and demand is sort of hand in glove. Yeah. if you will. Assortment would be more around Use to cover this company, i2. i2, yep. Yeah. Yeah. Yeah. Demand planning. This poor company, i2, got Nike's demand plan. Yeah. Absolutely dead wrong one quarter. Yeah. That's- They- That's no bueno. They. Yeah. Got fired on the earnings call. Yeah. The CEO admitted. On the earnings call. Yeah. The CEO- Rough. The Nike CEO blamed their miss on i2. Yeah. Right? Mm-hmm. This stuff is really important for retailers. Very important. Right? Yeah. Yeah. What happened to it? Is it Manhattan? They were acquired. They're still out there. Oh. Oh. Who bought them? Yeah. I have to go back and look. I left before they were acquired. Okay. Yeah. Okay. I joined PTC. I ran their augmented reality business unit, working for Jim Heppelmann. Ran product marketing, sales for augmented reality. That I know nothing about. In the manufacturing space. Why do they even have it? Gosh, we could spend the next 19 minutes and 13 seconds talking about that. Yeah. I think the real focus there is so PTC does manufacturing software, primarily tied to things like CAD- Yeah. product lifecycle management. Being able to visualize through augmented reality, how those systems come together, how to do break- fix, how to do maintenance. Oh, yeah. How to understand, how to repair some of those machines with augmented reality is an emerging area of interest in the IoT space. Yeah. You're still in Boston at this point? Yeah. I was there. Right. Yep. Okay. The phone rings. Phone rings. What gets you to TDC? Yeah. Yeah. Who's calling? Is it a recruiter or is it someone from the company? It's a recruiter. Who's recruiting? Yeah. I did happen to know a couple folks there. Yeah. Yeah, I mean, I've known about Teradata since I was very young. They've been around for a long time. Was really excited about the opportunity at Teradata, knowing what, especially from my SAS days, what they were capable of, from a performance perspective. Mm-hmm. Kind of missed the cloud bus, if I'm being honest. Like, I felt like being able to bring, at PTC, I helped them get to a software as a service business model with augmented reality and really being able to take the notion of platform as a service or software as a service. I prefer software as a service as a moniker because I think that it's actually more impactful to what we want to do from engineering and product value perspective. Thought that there was tremendous opportunity to help transform Teradata from where they were to where we could be in the market. Yeah, 'cause when you were, when you were working with them at SAS, I mean, it was just an appliance, right? That's right. Yeah. Yep. We're all in on SaaS. You'd have these huge companies that had tons of these appliances. Huge companies. Yeah. You couldn't replace Teradata if you tried. Yeah. They had so much rich domain expertise of what the customer was trying to do. Yeah ... that the stickiness was just enormous. Yeah. That continues today. I have a friend. He's doing something else now, but he was a salesperson at Oracle. He would try to replace Teradata. Yeah. I would call him up, and I'd go, "I hear that, you know, whatever company is planning to replace Teradata," right? He'd go, "Wallace, every company has a five-year plan to replace Teradata, and they keep buying more." Right. That's right. Again, that was pre-cloud. Yeah. Yeah, you know. Yeah. That's. Every company. That's the reality. Has a five-year plan to replace Teradata, they keep buying more. Yeah. It's incredibly sticky. Yeah. Okay. As soon as the phone rang, you're like, "This should be interesting," or did you have to spend some time- It had been a while since- Yeah ... really understood where Teradata was. Yeah, I spent some time really understanding what we were looking at doing. Yeah ... both the opportunity and the challenges. I think the product was underdeveloped from a cloud perspective, and I think the business at the time, didn't have the vision that we have today. We brought on Steve McMillan. Yeah ... shortly after I joined. Let's go through it. Yeah. You joined in 2020. Yeah. What did you find? Yeah. I joined, November of 2019. November of 2019. Okay. I found that I had a new boss. The CEO changed the day that I joined, which was very exciting. Oh, Steve came in the same day? No. Is this a different? Oliver left the same day. Okay. It was a very turbulent time, right? There was a lot of change- Yeah going on. I think there was an opportunity to really form a strategic objective focused on the cloud. Steve brought it and did that for us. He joined, what, about six months, you say, after. June. Yeah. June 2020. Yeah. We then set upon a cloud-first journey, which been it's been amazing ever since. Steve brought on some other excellent executive leadership members. Claire. Mm-hmm ... Chris's boss, as our CFO, has been awesome. Really, I would say we have been extremely aligned about what our mission is with our customers in the cloud. Steve comes in. Yeah. I don't wanna go too fast. That's okay. Steve comes in and he's like, "Okay, you know, we were 70% clients, 30% cloud. Now we're gonna go..." If I'm remembering right, it's been a while. Mm-hmm. Now we're 70% of our energy is gonna be on the cloud. Mm-hmm. You're the Head of Products, you're in charge." What do you do? Yeah. Like, you're given that marching order. What do you do? How do you affect that kind of change? Yeah. The first thing is you lead with data and voice of customer, right? Okay. Back into the engineering organization is, you can take a top-down approach to that, but really what you need are missionaries who are gonna go out and really understand the mission that we have and what our customers want. Our team of experts cares passionately about our customers and delighting them. It was really educating them with what our customers want to do now and where they're going in the future. Mm-hmm Which is a cloud world, right? It's a multi-cloud, hybrid world. We say cloud first, not cloud only. Then we went through and line by line, understood who was working on what and did a full- You did. We did. Wow. There's a little stick, a little carrot, really focused on making sure that we made a successful transformation. We inverted our R&D spend from 30% cloud to 70% cloud, and now we're at 80% cloud. We measure that on a monthly basis and make sure that we are focused in the right places. Right. All the engineers come up to you too. They do. They do. Okay. Yeah, you literally had to go through team by team. Went through team by team. Yeah. Made sure everyone had the right- Did you have the right skill sets? In many cases, we did. Yeah. In some cases, we did not. We've had some good rock tumbling and team tumbling to make sure that we brought in the right leadership, and the right hands to keyboard folks to make sure that we got to the cloud successfully. Man, we have some brilliant people who've been at the company for a very long time. Yeah ... and really understand from an engineering perspective how to meet a price performance model no matter where we're deployed. That has been really our calling card in the cloud is lowest cost performance at scale to be able to really deliver what the competition struggles to deliver, which is you can start small and at Teradata, as you spend more and as you grow more, that cost per query is the lowest in the business today. Okay. 2020 - Yeah you guys, you gotta get a bunch of customer stories, you gotta get a bunch of data, you gotta go through the entire team, make sure everyone's working on the right thing. What was the first sort of big deliverable on the, on the? So in 2020 - Yeah we were already in AWS and Azure. Yeah. In 2020, we, rounded out our, offers and deployed on Google Cloud. Mm-hmm ... which was exciting to sort of be there from a multi-cloud perspective. From there, we continued to create new value opportunities for our customers and for our sellers in the analytics space. Yeah. So that was- What was the next big release after you joined? It was Vantage on Google Cloud. Yeah Would have been the big release there. Since 2020- It's a stupid question, but why is that a lot of work? Why is that a lot of work? Yeah. Why can't you use the same version of Vantage on AWS and Azure and Google Cloud? Yeah. It's the underlying tech stack is largely the same, but you wanna make sure that you're integrated into the cloud-native capabilities within Google, AWS and Azure to make sure that from a performance perspective, that we hit the SLAs that our customers are looking for in any cloud that they're out there with. We have an exciting product which we've actually really doubled down on called QueryGrid, which is being able to make sure that you can get to data wherever it is, and so making sure that that performed at the right levels in Google Cloud was important to us as well. Yeah. Do you have the same sort of fundamental architecture as Snowflake does, where they are using the native storage of the hyperscalers? Yeah. Back in 2020, the answer would have been. You did not, right? Right. Okay. That's what I'm trying to get to. Yeah. Yeah. Yeah. Last year. What did we call that old architecture? Teradata Vantage Enterprise. Okay. Yeah. It's actually been incredibly successful, I'll just say. Like, for customers who are looking to migrate to the cloud quickly, they wanna shut down their data centers, they wanna get to the cloud quickly, Teradata Vantage Enterprise has been very performant, very easy move to the cloud. You're talking about maybe a couple of months to migrate. Mm-hmm. More often it might be three or four months, but we've got lots of examples where it's a couple of months to move to the cloud. That's virtually impossible with anybody else. Yeah. That's an exciting aspect. To your point, there were some opportunities that we saw. We saw some opportunities in full separation of compute and storage. We saw some opportunities in full support, at a native level, of object storage. S3, for example, on AWS, Blob Storage on Azure. We started a journey in that direction as well. Okay. To interject, what Hillary was just talking about with the VantageCloud Enterprise product really helped to catalyze our growth in the cloud by six-fold from the time that Steve started till our last reported earnings, which was this past February. Mm-hmm. Growing from about $50 million to almost $300 million, you know, was a primary driver, was Enterprise. Yeah. Yeah. Is it too simplistic to think about it as, effectively hosting? Um, so- Well, like what SAP's doing with- Yes, because it's not. ... with S/4, right? A whole bunch of it, you know, Dow Chemical. Yeah They're not on some multi-user, right? Mm-hmm Multi-tenant thing. It is basically S/4 for Dow Chemical that happens to be at Amazon. Mm-hmm. It's worth combining. Yeah. It's actually, that's a common misunderstanding. Is it? Okay. it? Okay. Yeah. When we, when we moved to the enterprise and the cloud, product offer, we from day one, took advantage of commodity available hardware, in the cloud providers. Okay. We didn't move one of our appliances into the cloud ever. Yeah. Yeah. Yeah. We took advantage. This is when you asked about, you know, why is it so hard or why is that a big deal. Yeah. It's because we are taking advantage of the different configurations that the CSPs provide. That's important to our customers, so you can contract in the marketplace. It's what makes it not just a hosted environment, but it makes it truly a cloud offer. Yeah. Like, someone recently explained to me what Oracle Cloud customer is. Yeah. It is. I go, "What is it?" He goes, "Well, we have a cage in our data center that's red. Yes. I go, "Come on. Yeah. He goes, "They, their people come and service us, and they charge us on a monthly basis. Yeah. I go, "It's still in your data center? Yeah. Yeah. Yeah ... that's not cloud. Yeah, that's not cloud. That's not- We didn't do that. Yeah. We didn't do that. We don't consider that cloud when we report out to the street. We don't count those dollars. In their defense, he did say, "You know, it's funny though, because It's getting us there. Right. Right? Now they own it. Yeah. Now they wanna put it into another data center. Yeah. They wanna keep serving us, and they take us. Yeah, well, we'll do it. Yeah. Okay. So we moved to the cloud. Yeah. What were the two things you said were super interesting? You said. Separation of compute and storage and full support of object storage. Separation, yeah, and full support of object storage. Let's talk about it. Yeah. It's really important, right? Yeah. Let's talk about them. Why are they so important? Yeah. Historically, from our perspective, our customers have been limited to a fixed environment. Yeah. They know what they can get out of a fixed environment, how many queries they can do. Mm-hmm What the SLAs they can hit, but it's hard to grow. To grow, you would have needed to do a migration into a new environment, right? Think of physical servers. Even in the cloud, if you have a constrained environment, which arguably Enterprise is and was, it's difficult to grow, through a consumption model. We've done some really exciting and interesting things. One is with VantageCloud Lake, which we just, launched in August, went GA beginning of this year, we have full separation of compute and storage. That means that, you can scale up compute separately than your storage. Storage, I don't know how many folks... How many folks in the room totally understand separation of compute and storage? Yeah. Okay, cool. Say it in plain English. Let me just, let me break it down just for a second. Yeah. It's always good to understand. If you think on your laptop, right? You've got compute and storage, and it's kind of fixed capacity. If you need to store more photos on your laptop, you're gonna have to buy like an external drive for that. If you suddenly wanna open up a bajillion different Excel spreadsheets and do a bunch of really, like you guys do fancy math, right? You wanna do a bunch of fancy math, you're gonna have to get a new laptop with better compute in it. In the cloud, right? You have the ability to separate those things. I want some really high-end compute to be able to do some really exciting analytic work. I want some maybe less performant compute in order to do some more standard things. I know if I'm a retailer, for example, I'm gonna spike in Q4, and I need to do a lot of compute during the time that I'm getting a lot of transactions. Separately, you have storage of all of your data, and we have always had hot and cold storage. Storage that is like, "Oh, I'm gonna need it right away," and then maybe more archival storage concept. Now with our ability to separate those things, you can store a lot more data separately, and then you can spike on your consumption with Compute. That means that if you want to spin up a new data science team, and you wanna give them maybe a fixed amount of dollars that they can go and spend, you can do that with Teradata today with our VantageCloud Lake offer. Historically, you would have to argue with IT to go and get some of that capacity. What does that mean for our customer base? That means that in a fixed capacity environment, they can now add some new use cases using the data that we already have and new data sources that they're bringing to Teradata and be able to, in a more elastic way, so that's the technology side, more elastic, scale up, scale down. From a value perspective, IT is no longer worried about hitting their Service-Level Agreements with their reporting that they're doing or their analytics that they're doing. They can run these new exploratory use cases outside of the SLA-driven workload. If you're a bank, if you're a retailer, if you're a telco provider, you can say, "I know I can close my books successfully. I know that my e-commerce site's not gonna go down. I know my reservation system isn't gonna go down," all of those things running with Teradata today. And I can afford to go and do some experimentation with this separate compute that I'll pay for on a consumptive basis, and go and understand my customer journey mapping and what my next best offer should be to this customer. That is super exciting for us and really exciting for our customers. When we launched this new product and we went out and talked to customers, it was literally like, "I can't believe we didn't have this a year ago. Mm-hmm. We're so excited that we can do this with you today." For us that means that we have two price models. One is fixed capacity, so I know I'm going to spend only, you know, $5 million a quarter with you. We also have a more flexible price model that's consumptive in nature, and that gives us great flexibility in terms of how we sell. It also, in this market economy, means that our customers can sleep well at night knowing that they're not going to run a bunch of work and spend all of their Q1 budget at one time. Yeah. IT is no longer worried about hitting their- SLA, Service-Level Agreements. If you're IT, if you're a bank, you say, "Great, every Monday morning you're gonna get a report." If you're a store manager, "Every Tuesday morning you're gonna get a report. Yeah. Those reports have service levels. Your boss wakes up, and they're like, "Where's my report?" You're like, "Sorry, some data jockey did something dumb on the system. Yeah. Now you're kind of in trouble. That's not gonna happen. Yeah. This is a real thing, right? Like, at the end of the month- Yep. You couldn't have finance closing the books and. Marketing doing some experimentation. Yeah. Right. Yeah. We've fixed that for our customers, which is exciting. When was this generally available? At the beginning of this year. Oh. Is it out? Is it generally available yet? Yes. It's GA now. Okay. Yeah. just to- Like February? January? January 1st. In January. Yeah. Okay. Just to translate what Hillary framed into the financial profile of the company, you know, certainly with the two products, Enterprise and Lake, which are complementary to one another, this helps to inform our confidence level with regard to reaching the over $1 billion target of cloud ARR in fiscal 2025, driven primarily by migration and expansion activity, but also with net new logos entering the company. The products will help inform and grow wallet share, potentially at existing customers, but also be an attractor to that net new technology that we're offering. It's the same Teradata technology that you had in our heritage, but we've brought it all to the cloud with the performance of the cloud. Yeah. Okay. Just so I get a good soundbite. How has the launch of VantageLake gone so far? Yeah, look, I think the traction has been pretty positive. We've had some very notable customers who sign up in beta. The interest from both a direct sales force and leads, as well as the indirect channel, largely through the growing of our partner ecosystem and the SIs who are helping to promote the idea and build a real book of business around it gives us a lot of encouragement. The fact, w ith this offer, with VantageCloud Lake, we are now able to offer a customer, a $5,000 a month offer, which means that if you are a large bank or a retailer and you want to spin up a small environment, you can do that at a price point that previously would have been impossible with Teradata. We see that expansion, as Chris was just talking about, this expansive opportunity as well as new logo opportunity to be really exciting when it comes to VantageCloud Lake. Really quick, 'cause the analytics piece is so important to us. We also launched. You have 15 seconds. I know. ClearScape Analytics. ClearScape Analytics was taking a lot of the goodness that we had in the analytics space, and adding even more analytic capabilities through ModelOps and additional time series forecast capabilities. This is a huge differentiator for us in the market. Gartner just came out with a report that said we are number one in all four analytic use cases, and this combined with the separation of compute and storage really allows our analytic customers to go out and do even more AI and ML at scale with Teradata. All right. Sounds pretty good, right? Where's the stock? Do you know? $40-$42, somewhere in that range. Yeah. Yeah, $72 target. Sounds pretty good to me. All right. All right. Thanks very much, Hillary. Thanks so much for having me. Yeah, nice having you.