Thanks, everyone. I'm Derek Wood, Senior Analyst covering enterprise software. We have Steve McMillan, CEO of Teradata. Thanks, Steve, for coming.
Derek, it's great to be here.
And a reminder, II Voting starts next week. We appreciate your support. With that, let's dive in. I mean, we're coming off of Salesforce's earnings last night, and there's been a number of companies that have talked about softer conditions in Q1. So would love to kind of get your take on what you've seen in the macro, what kind of buying behavior you've seen really over the last year, and how that's evolved.
Yeah, I think, certainly for Q1 and Q2, I think we've seen some spending restrictions in the environment. I think it's going to free up as we move into Q3, Q4, as we move into the second half, just to the super macro level. The great thing is, from a Teradata perspective, that CIO spend, if you look at the categorization of CIO spend, you know, AI, data, and analytics has overtaken cybersecurity now in terms of priority for spend and spend analysis. I think what's gonna happen as we move into the second half of the year, you're gonna see organizations moving from kind of proof of concepts around some of the AI solutions that they've had into real production-oriented solutions.
So that's gonna be an exciting catalyst and tailwind, I think, for the entire data and analytics marketplace. And then, if you look at it from a geography perspective, we're seeing some real success in what we call our international, so that's EMEA and APJ. The teams there are doing a great job. I think organizations there are kinda a little bit behind the US in terms of their data analytics and AI strategies. And so we see that spend environment continuing. But as we move into the second half of the year, I think it's gonna free up in terms of the opportunity that's in front of us.
Okay, you brought us right into generative AI. Maybe I'll go there before I touch on some other subjects. So what I think you did have a new product that, or a new solution that came out, was announced in the last couple of weeks.
Yeah.
Could you give us a sense of what the strategy is there?
Yeah. So, you know, we've always had a great capability in the Teradata platform for AI and ML functions. And in fact, in August 2021, we announced ClearScape Analytics, which was essentially taking AI and ML functions and embedding them right into our database engine so that you can run complex data and analytics at really super high enterprise-scale performance levels. Interestingly, just two months before all of the interest around ChatGPT came out, if you think that's just November 2022, when that happened. So, it's interesting in terms of looking at how that marketplace has evolved. Just from a generative AI perspective, we have a very open and connected viewpoint from OpenAI. So we have a kind of bring your own model. So bring your own language model.
You can run it inside the Teradata environment, and you can actually trust the data that you're feeding into that language model because it's all the highly pristine data that you run your company on a day-to-day basis. So it reduces the hallucinations from a language model perspective, gives organizations a real ability to have a trusted AI. In fact, we did a survey recently that will be up on our website asking C-level execs what they thought about AI and what their key challenges were from an AI perspective, and trust really came out as one of the key areas, trust and security. So making sure that your data isn't like made available to the general populace in terms of these generative AI models that are out there.
Just from a business perspective, we see it as a real tailwind for us. As you said, we launched a product called AI Unlimited. It was featured at the Microsoft Developer Conference. It was great to have, you know, the Teradata logo up behind Satya as he was talking about Fabric and the Microsoft Fabric. Having Teradata being able to integrate right into the Microsoft Fabric, utilize all of the advanced services of Azure from an AI perspective, has been a real catalyst for us.
Okay, so it sounds like you don't have any plans to build your own large language models. Do you wanna be Switzerland and enable companies to bring-
Yeah, bring your own.
W hatever, open source, something that's been commercially built, OpenAI, whatever?
That's exactly right. I think, you know, the language model battle hasn't even been fought yet-
Mm-hmm
In terms of who who's gonna win. So, you know, OpenAI, certainly a fantastic capability. But, you know, everybody's developing their own language model. A lot of them are what you might call large language models, so they're ingesting, you know, tons of data from lots of different sources. We actually have a viewpoint that the value from generative AI will actually come more from medium-sized language models or small language models that are trained in particular solution areas, be it customer experience or supply chain optimization, because the cost of running these large language models can be considerable.
Mm-hmm.
And one thing that, from a Teradata perspective, we're very interested in financial governance. So how do our customers control the cost of running their data, analytics, and now AI environment? And that's something that we can bring to the table, help our customers put in place a really trusted GenAI solution. I think the other thing is, if we actually look at where are organizations getting business value from AI today, it's not as much in generative AI. Generative AI is a nice way to present that to, you know, your, your users or your customers or consumers. But really, predictive AI, descriptive AI, some of the more traditional functions around that is, in machine learning, is really driving a lot of business value today.
Mm.
That's where we see a lot of investment from our customers.
Okay. Does Teradata support unstructured data?
Yeah.
Obviously, structured SQL is a big core part in transactional data, but, yeah, I mean, how-
Yeah.
Cause that's part of the new opportunity with Generative AI.
Exactly.
You know?
You know, I was talking to one of our customers, a bank in Canada, and they were saying, like, they have 10x the data in object store,
Mm
T han they do in their enterprise data warehouse. So as we've looked at, you know, how do we support object store, how do we support streaming data, you know, how do we support things like video data directly from the platform in native object store, we've got customers now developing solutions that do just that, be it, you know, robots on the production line streaming data into a native object store in AWS S3 storage, or, you know, a restaurant chain taking video data, looking at the queuing system, the, the queues that they have in the restaurants and how to process that data. And so these are all capabilities that are built right into the Teradata platform today.
Some really advanced analytics that our customers are just starting to use, and we see it as a great expansion opportunity for us as we move forward.
Okay. The other new product development, I think, is around open table formats.
Yeah.
I think you guys announced that last quarter with support for Iceberg and Delta from Databricks, or no, I think. Well, yeah, they built Delta. But those are both open source.
Yeah.
So what's the strategy behind that? How are you unlocking additional value? Why did you start supporting those open-source table formats?
Yeah, I think open table format, you know, it gives a real opportunity for organizations to use, cheaper storage, object store storage, but then develop a kind of lakehouse construct around that. So structuring that object store data, utilizing, open table format, gives a, a low-cost, capability in the market to-
Okay
R eally have that structured data in place. We saw it as an opportunity to increase our TAM-
Mm
E ssentially, in terms of being able to access that open table format data. And we went into it with a very open mindset in terms of both supporting Iceberg and Delta. The way our query engine works, we can support multiple different table formats as we move through time, and it's getting a lot of interest. In fact, it's picked up more and more over the last six months in terms of organizations thinking about how to modernize their data environment, utilize an open table format. And the way that we talk to our customers about it is, look, you're always gonna have to have that, what we would say, gold standard of performance from a storage and a structured data perspective, and maybe your enterprise data warehouse that you use to close your books every quarter.
Then you could have a silver tier, and the silver tier for us is essentially Teradata managing object store, utilizing our file system. That's our kind of second tier of performance capability. And then the third tier is Teradata querying open table format on native object store. And so our strategy there has been, you know, how do we make that, OTF or native object store as performant as possible? If you think about the one thing that Teradata is known for is our enterprise price performance.
Mm.
So how do we get that open table format data towards, not on par with our gold standard of storage, but how do we improve that performance so that that data can become useful for organizations?
Yeah, that's a helpful landscape of the canvas that you're going after. Is open table support for open table, is that fully generally available now, or what's the timeline for that?
Yep, it's fully available in our VantageCloud Lake product. We're gonna continuously develop that capability to improve the performance, bringing some of our secret sauce to the table in terms of improving that performance of open table format.
Will that have any deflationary impact to storage revenue for you guys if customers are saying, "Hey, you know what? I'm gonna take some of this data that I've stored on Teradata, and I'm gonna push it out to a cloud object store." Do you-
Yeah, I think, what we see there is that our, our customers are always gonna have to have, a lot of investment in what we would consider that gold tier.
Mm.
So Teradata managing a Teradata file system on block storage. And our customers run absolutely mission-critical, enterprise-scale workloads and solutions inside the Teradata platform, where that kind of silver and bronze level performance levels don't meet their business requirements. And so the interesting thing is, even if you, and we, we see this, even if you take the customer master record, and you put it into an open table format, in order to close your books every month, you still need that customer master record-
Yeah
I n the gold standard of performance-
Mm-hmm
T o close your books.
Mm-hmm.
And so we see making available these other tiers of storage and data constructs as something that's gonna expand our opportunity inside our customers.
Okay. I wanted to shift gears and just talk about, obviously, a big part of your model is getting customers over to the cloud, and you see better expansion rates once you do. Where are we in that journey? Does AI accelerate the interest in migrating to cloud? And kind of, what percentage of your base do you think will get to cloud over the next few years?
Yeah, so I think, you know, we've done a great job. We've gone from essentially a very nascent cloud business to over $500 million at the end of last year of cloud ARR. So four years developing that $500 million of cloud ARR has been a tremendous achievement. I think we do see the interest in AI and really generally the desire to utilize cloud-native services. So if it's Azure ML or OpenAI services, we see that as more of a catalyst to move some of the workloads into the cloud. You know, if we look at our general customer base, you can think about it, you know, we've got kind of $1.5 billion of ARR.
We've moved about $500 million of that into the cloud. 70%, 70% of the customers that run in the cloud with us also still have an on-prem capability, and our ability to execute hybrid cloud environments, I believe, is second to none. And so we've still got a long road, in terms of, the opportunity to migrate customers to the cloud with us, and obviously, when they get to the cloud, they really grow with us. But we always see that due to regulation or data sovereignty or just the security standards that our customers want to implement, that we will have some customers that will always remain 100% on-prem.
So then it comes into play in terms of our partnerships with organizations like Dell, in terms of running on their converged infrastructure in people's data centers. That enables us to focus and become more and more of a software business-
Mm-hmm
A s we move through time. Software and cloud is clearly our strategy as we move forward.
Do you, you guys do have an advantage of being able to offer hybrid over some of the pure-play cloud vendors. Is there an appetite that's changed to actually kind of move more workloads or keep more workloads on-premise for cost reasons?
I think, our customers are seeing two things. One, there's. If you look at some of the banks and financial services environments inside the US, there's a question around regulation.
Mm.
You know, what regulatory compliance are they gonna have for the data that moves into the cloud? And we see that a lot in Europe as well. We also see data sovereignty requirements like making organizations want to stay in the cloud. And also, I think, really super large enterprises, we focus on, you know, the G1000, the G10,000 now, they will always have enough scale to essentially have data center environments that they can operate at scale very effectively and efficiently. And so I think the reason that organizations are now using the cloud is to get access to these advanced services-
Mm.
-to get access to things like, the machine learning or AI services that are, the CSPs are making available. But our focus now as well is: how do we make those services available on-prem? So, working with, organizations like Dell, how do we start to enable, companies to have all the advantages of, running in a CSP environment, but giving that to them on-prem, in terms of running a language model on-prem in, say, the Teradata environment?
Yeah.
That hybrid world for us is a key catalyst for us.
Mm-hmm. Okay. Okay. Can we just touch base on kind of recent execution? You had had a couple large customer losses that had been in the works for a while, and then there's been some tougher, you know, sales cycles where deals have pushed. First of all, on the large customers, how do you feel about retention of your remaining top 20, top 50, whatever you wanna call it? And let's start there.
Yeah. So I think if you, as we said, as we looked through our earnings, and as we plotted out the 2024, we did see, we knew about some erosions that were gonna happen in terms of our customer base. These have been in the works really for three or four years, before we had the cloud offering that we do today. And indeed, so one of those customers in particular, they wouldn't accept in an evaluation, any product that hadn't been GA for 12 months.
Mm.
And so, we knew about these, these major transactions that were going on, and we'd factored that into our guidance for the year. I think as we look at our customer base, and to your point, all, all of our top customers, but not only that, all of the customer base, we have a really good idea of what's going on inside our customers, and, we see great opportunity to drive more and more value for that, customer base over time, as we continue to invest and innovate in the platform that we've got, as we demonstrate how we can migrate them to the cloud for certain workloads, take advantage of those advanced services and advanced workloads.
We don't see any change, in terms of our customer environment or the marketplace environment, and it gives us confidence as we look out into the second half of the year in terms of our execution against the guidance that we put out there.
Okay. Just in terms of go-to-market, let's talk about that. You have a new CRO. He's already been at the company for a while, but any kind of changes that you'd highlight that have been kicked off this year?
Yeah, I think putting our new CRO, Rich Petley, in place has been a great advancement for us. You know, as you said, he's been with us for a couple of years. He started off by running our EMEA division. He's been promoted sequentially through the time he's been with us to run international and now the global team. He's had terrific success. So he knows our business, he knows our technology, he knows our customers, and he's been a real driving force, really, in terms of starting to get new logos into the Teradata ecosystem. And so, getting him to be able to take that approach, take that experience and applying it on a global scale is going to really continue the lift for us as we move forward.
Did you give some stats last quarter on new logo pipeline of new logos, and-
Yeah.
Any other stats you want to share?
Yeah. So we've over the last three years have really consistently increased our focus in terms of winning new logos into the Teradata platform. A lot of it is dependent on the product. So our VantageCloud Lake product, it only went GA in January of last year on AWS. It went GA in June of last year on Azure, and it's going GA in Google Cloud in the next month or so. That's opened the aperture up for us in terms of winning that new business. And over the last few months we reached a milestone that I thought was important to highlight on our earnings call, which was, you know, just in that two- or three-month period, we'd seen over 100 new logos come into our pipeline.
I think that is really a testimony to the fact that we've now got the right product, the right, right sales motion, and the right value proposition for our customers, that's enabling us to compete and engage in the marketplace in a different way than we have previously.
And just give us any color on what, like, average sales cycles are. I mean, do you think that that's been a pipeline building for the last year, and you'll look to convert more of that this year, or?
Yeah, I think if we look at our sales cycles, they average around 9-12 months, right? So an enterprise software sales cycle. Yep. So, that I think we're all very experienced in. Certainly, we see some opportunities convert pretty quickly, especially from an AI perspective, as there are specific use cases that we can bring to bear. And, you know, if I think about, you know, what's going to drive our growth and what's driving the interest in those new logos, it's us having a differentiated value proposition around trusted AI. It's us being able to take an industry value proposition and use cases. You know, we've got over 40 years of delivering the most advanced use cases for the biggest organizations in the world.
That's enabled us to generate a lot of intellectual capital from an industry perspective. And then I think the third thing is, interestingly, is the reemergence of the interest on on-prem and having things like AI in a box that we can deliver on-prem, and a roadmap that our customers see in terms of our on-prem technology set, converged infrastructure, really super interesting, I think, for a lot of the markets in EMEA and APJ.
So if you're in a bake-off with Snowflake or Databricks, those are some of the competitive differentiations that you guys-
Yeah, and that hybrid capability.
Hybrid.
And also enterprise price performance.
Got it.
For the types of workloads that these big organizations operate and execute, we operate at an order-of-magnitude difference in terms of price per query. And so a lot of organizations are seeing that the cost of these cloud-native solutions can spiral out of control. We've always had, inside Teradata, because we were born on-prem in a limited capacity environment, the ability to execute really complex and large workload in a confined compute environment. So we solve really difficult problems with great software.
Yeah.
If we look at our competition, because they were born in an environment where you could scale compute dynamically to solve a problem, that's exactly how they address their workload management and workload issues. So they will scale out their compute environment to address more and more complex queries.
Mm-hmm.
That drives the cost up in terms of running these platforms compared to Teradata.
Okay. One of the other things on the go-to-market side you guys outlined is investing more in customer engagement. What does that look like? I mean, obviously, getting more growth out of your base, more dollars out of your base is a way to unlock a higher growth-
Mm-hmm
I n terms of top line for you guys. So what are you trying to unlock with your kind of greater focus on customer engagement?
Yeah, I think, you know, great customer relationships turns into a great business for us. And we can see it in our net expansion rate. So once we move organizations to the cloud, we expand them. And so if you look at our net expansion rate, it was 123% in the last quarter. We expect that to continue at over 120% as we move forward. And it shows that as customers move to the cloud with us, they grow with us in the cloud, that we become more sticky inside that environment. The really interesting thing is, and it goes to the point in terms of how we look at the overall customer base.
If you look at, if you take our cloud business and the cloud growth that we have and put that aside as a, you know, a business that grew 48% year-on-year in a market that's growing around 30%, way ahead of Snowflake in terms of percentage of year-on-year growth, and you look at our on-prem business, after you take out migrations, our on-prem business is actually really solid. It's flat to slightly increasing, which is directly in line with the on-prem marketplace today, but we see an opportunity for that to increase over time as we move into the future from an on-prem perspective.
So we've got a really solid fundamental in terms of our on-prem business and the customers that we have just now, and then that hypergrowth that we see in the cloud is just building on that in terms of our execution capability.
So, to get to a double-digit growth profile for Teradata or yet, you know, around a 10% level, what is it to—I mean, it sounds like moving more customers to the cloud, greater focus on-
Yeah, I think-
greater new customer logos.
That's right. I think if you just do the math, yeah, so if two-thirds of our base is still, like, on-prem, at flat to slightly increasing, and our cloud business is growing at 20 points plus, then as cloud becomes more and more a significant part of our number, as our cloud ARR goes over half of our total ARR, then that will start driving that high single digits, low double digit. But remember, we've got that really solid on-prem business that is essentially enabling us, in combination with our cloud business, to give a commitment for next year to deliver $450 million of free cash flow.
Wow!
So what you've got in Teradata is a company that has a great cloud proposition, growing really strongly in the cloud, maintaining that on-prem business, and also generating $450 million of free cash flow.
Okay. Yeah, those are good targets for t hat's for next year, right? $450.
Four fifty.
Any questions in the audience? Okay, I wanna talk about seasonality. We've been seeing this from other companies recently, and you as well.
Mm-hmm.
That it does seem to be more of a, like, seasonally lower first half, hockey stick second half. Is that what you're seeing this year?
Yeah.
What gives you the confidence in seeing that ramp in the second half?
Yeah, I think, as we talked about the macro, that's really translating directly into what we see from a customer spend perspective. We did see elongation in deal cycles that we factored into our guidance for this year, and I think it was really as organizations took a step back to look at their data and analytics environment. We had some customers, just as an example, switch from, you know, "Oh, we're gonna go Google," to switch to Azure because they saw that Microsoft was really embracing much more that AI service capability. So I think those became much more strategic decision-makings. As I look at Teradata, Q1 is always seasonally our lowest growth quarter. It's our highest renewal quarter in terms of execution, and Q4 is always our highest.
So we always expect at least 50% of our total ARR growth, many times more than that, to come in Q4. And as we look through, we know that our Q2 is gonna be better than our Q1, our Q3 is gonna be better than Q2, and we're gonna do more than 50% of our growth in Q4, which again, is part of that enterprise, software sales motion-
Yeah
in terms of execution.
Okay. Anything to highlight in terms of new partner initiatives, whether it's with the CSPs or?
Yeah
-the GSIs?
Yeah, really happy with the interaction, clearly with the CSPs, especially with Microsoft. Being a part of their new Fabric announcement, I think is gonna generate a lot of tailwind for us in terms of interest in the Teradata platform, and then taking that interest in those services and turning them into bigger opportunities from a VantageCloud Lake on the Microsoft platform. That's gonna be super interesting for us. In terms of other partnerships, Dell has been a great partnership in terms of getting the Teradata platform super performant on Dell's converged infrastructure, and then Dell's focus on, you know, providing an AI hardware on-prem solution and taking advantage of that inside the Teradata platform should be super interesting. And we're doing some great work with the GSIs, a great partnership with Accenture.
They've trained over 2,000 people now in the Teradata ecosystem. But also, I would one of the really interesting things is our work with the regional SIs and some smaller partners in terms of, specific solution sets and industry-based solution sets that we can take to our customers and deliver real value very quickly for them. That's been super interesting.
Can you just, we have a minute left, but just unpack what's new with Microsoft and Azure-
Mm-hmm
Because I think that sounds important. Fabric is new for them. You guys had a big announcement at the Build conference.
Yeah.
There seems to be something that's kind of upticked in terms of the engagement with Microsoft and Azure.
Yeah.
A little more color.
Yeah. So, we've always had a great partnership with Azure. In fact, if you look at our cloud presence, we kind of reflect the CSP market share. But we're finding that our customers are more and more looking at Azure and Microsoft from an advanced services perspective and AI services, and how do we- how do they integrate data that may be in on-prem systems up to the cloud? How do they develop and deploy experimental solutions and data science-based solutions? So the AI Unlimited product that we actually announced has all of the capabilities that are in our enterprise product from an analytics and AI perspective, and making that available in a serverless query engine on the Azure environment.
Yep.
If you think back 2 years ago, that just is a great demonstration of how Teradata is a completely different company-
Mm-hmm
I n terms of, you know, we would have never had that concept of a serverless query engine running natively in one of the CSP environments, and that's what we've got in both Azure and AWS today.
Okay. Okay, great. Thank you, everybody.
Thank you.
Thanks, Steve.
Hey, thanks, Derek.
Appreciate it.
See you.