Teradata Corporation (TDC) Earnings Call Transcript & Summary

Maybe talk about the adoption. You said you'd launched it in August of last year. I think the GA was beginning of this year, right. So it's not been too long, but what have you seen from customers? Is there -- is it a new logo story? Is there a migration story to it with VantageCloud Lake?

Yes. I think VantageCloud Lake has really given our customers a point of view of how they can take their data strategy forward. So from an existing customer perspective, it's given our existing customers some real confidence that there's an architecture that they see into the future that's going to be able to support their growth and support their data and analytics use cases into the future. But to your point, I think the other thing it provides is an ability to win new logos and smaller workloads. We are always going to be focused on the enterprise market. So the [ G 10,000 ] that's really the sweet spot for Teradata because we really drive enterprise performance and you can see that in the shape of the deals that we do. So we just referenced a 9-figure deal that we did in first quarter of this year. We -- back in the third quarter of last year, we actually did the largest AWS marketplace deal by an ISV, which is super powerful if you think about that. So a bigger deal than SAP or any of the other ISVs in the world, Teradata actually did that deal with Amazon, and we're super excited about the focus on the enterprise, the large deals that we can execute, especially in this market, what we see in this market because we are not exposed to some of the challenges that some of the SMB customers are having just now. The enterprises still want to utilize data, they want to utilize cloud-based technologies to deliver into the future. And so that gives us a lot of stability around our opportunity base and stability around a revenue base as we move forward.

Yes. Let's talk a little bit about competition. It is an interesting field. There are a lot of new players. There are a lot of strong players. Snowflake. You have all the hyperscalers, their own things. Talk about how do you see that competitive landscape? Why do you win when you win? Why do you lose? Can you talk about just all that dynamic?

Yes, for sure. So I think we could probably segment the competition in the data and analytics marketplace into 3. It's kind of the traditional providers, the legacy providers, like IBM and Oracle. There's the hyperscalers, as you mentioned, and then there's the kind of born in the cloud, Snowflake or Databricks. We compete against all 3 based on our enterprise scale and performance and our price performance. So against all 3 categories there, we can beat them from a price performance perspective and enterprise performance perspective and an enterprise scale. Just an example of that, sometimes, as customers look to utilize some of these technologies, either from born in the cloud or the hyperscalers, they find that those technologies just can't operate at the scale that their organization and their business needs. So we had an airline in Europe, as an example, that was looking at one of the hyperscaler capabilities to move their platform to that hyperscaler. And what they found was they just didn't have the capability to execute. But then we have unique differentiation against each of the 3 categories. So to compete against the traditional providers. If you look at Oracle strategy, for example, Oracle strategy really orients around OCI, an Oracle Cloud. We are a multi-cloud capability. And so we offer our capability in AWS, Azure and Google. And that's very compelling for customers and enterprises around the world as they want to develop a multi-cloud strategy. Competing against the hyperscalers. Again, having that multi-cloud capability is a very compelling reason to utilize the Teradata platform, but not only that, being able to, for some of the largest customers in the world, also have an on-prem component of that capability as a real differentiator in terms of competing with the hyperscalers. And actually, we see that -- we just announced a large partnership with Dell, actually, so that our -- Teradata software can run on Dell's converged infrastructure and actually, Dell's Salesforce is now incented to sell Teradata software on top of the Dell converged infrastructure. And so that's a unique proposition that we've developed with Dell that will open up like kind of on-prem segment in the marketplace. And then competing with the born in the cloud, the cloud natives. I think what organizations are finding is that the cost of operating some of these cloud-native capabilities is incredibly expensive because their answer to complex challenges is essentially to scale up compute because they were born in the cloud, they're used to have an infinite [ in verticals ], infinite resources available to them. And so if a Snowflake or Databricks has to solve a really complex query or analytical use case, they'll spend up lots of compute to do that, and it starts to increase costs fairly significantly. So our approach to financial governance and query optimization and workload management enables customers to utilize cloud-based technologies in a very effective and efficient way, and that's really differentiated from the competition. So as we look across those 3 segments of competition, Teradata is really well placed to win business. I think a lot of our customers are moving to the cloud with us because they see those capabilities manifest now in terms of the technology that we've got and the acceleration that we see in terms of our cloud ARR growth. If you look in Q1, we grew our cloud ARR 89% from a year-on-year perspective. And that's a testimony, I think, to our technology strategy and the execution of the company.

Yes. The multi-cloud, the hybrid cloud, all those points make sense, the born in the cloud query part. Have you done any kind of studies in terms of similar workloads running in Snowflake or Redshift and Teradata. Have you done any kind of...

Yes, there's -- we've actually had third-party analysis. There's a company called BEZNext. They did some third-party analysis in terms of cost per query when you compare it to Teradata workload, execute and how that compares to Snowflake, how that compares to Redshift. And we've actually got that materially available. If you look actually at our last analyst and investor meeting, we have one slide in there that kind of highlights that data, and it shows an order of magnitude difference from a cost per query perspective. But the other thing I would point out in terms of external validation of the strategy is from a Gartner perspective, Teradata is in the leader quadrant from a cloud database management system. But more importantly, Gartner also looked at 4 use cases where the compared Teradata with all of the classes, a competition that we just spoke to. And Teradata was declared the first in terms of capability and enterprise data warehousing and logical data warehousing and analytical use cases and also operational databases. And so that Gartner report really gives a solid foundation in terms of -- and solid ratification of our technology strategy.

Right. Let's talk a little bit about macro. Talk about how -- what are you seeing in the macro environment? How is it impacting Teradata? And more recently, when you're talking to customers, what is the sense of the current kind of business environment?

So Teradata, we are an AtScale organization. We have 7,000 people across the world, and we operate across all industries and have in-depth knowledge of industries and industry use cases. Again, we're focused on the enterprise segment across the world. And so having that variation of industry and variation of geography, actually, again, gives us some stability to our performance and to our overall growth trajectory because as one industry may not be performing well, we tend to find another industry. As one geography may have a challenge, we find another geography that makes up for that. So having that dispersion of business from a global perspective, gives us some security in terms of our overall numbers and solidity in terms of our overall numbers. Because we're focused on the enterprise segment, we actually haven't seen much impact in terms of the macroeconomic environment, just now with higher interest rates, a lot of the organizations that we interact with aren't short of capital and capital investment. And indeed, those enterprise-sized organizations, they want to use data and analytics to respond to the challenges that they see inside their organization. And I think that's one of the reasons why data analytics is a category for CIO, has been maintained as one of the most important areas for investment for organizations. And so the macroeconomic environment, the reason that we were confident in terms of reaffirming our guide for the full year, was because we actually continue to see strength in our pipeline and strength in terms of execution as we go through the year. If I think about how we performed in this most recent quarter, you've seen that sequential growth from Q4 to Q1 from our total recurring revenues and our cloud recurring revenues and how we see that going through the year. We actually -- we were actually asked is that an inflection point for the company, right, as we're starting to grow those revenues. Now I wouldn't use the term inflection point. I think this is just a demonstration. And the plan actually in terms of how we set out the guidance for 2023, but also our long-term guidance to 2025 and having over $1 billion of recurring revenues in the cloud by 2025. So we actually see the opportunity to continue every quarter to consistently deliver. Q4 is traditionally our strongest quarter as we go through 2023, but it really sets us up for that long-term guidance as we get to 2025.

Yes. Understood. I want to see if anybody in the audience have any questions? Okay. We have a few hands.

Great. It's quite the transformation. You talked about making data easily available, liberating the data, it seems like sort of the Holy Grail in a lot of ways. So the question I have is, should that mean at some point you will start winning new logos?

Thanks for the question. Yes, we are actually part of the strategy change that I put in when I joined the company really was that we had stopped a new logo -- the previous management team has stopped new logo acquisition. They had essentially a theory that they could leverage the existing customer base and growth in data and the customers that they had in terms of the largest companies in the world would power growth. Now we certainly see that as an important growth aspect for the company as we move forward. However, our new approach and our technology approach starts to enable new logos. So we've started to see the traction in new logos. What I would say for 2023 and then a macroeconomic environment is difficult for all customers -- all organizations and IT organizations to win new logos, unless you're doing a platform consolidation, a cost takeout consolidation. So I'm pretty happy with the progress that we've been making from a new logo perspective. I've used the -- it's kind of de minimis in our 2023 guidance, but it becomes increasingly important as we move to 2025, but more importantly, as we move beyond 2025. So the goals that we set up for 2025 are achievable even with a very small amount of new logo. So we see that as a real upside as we move forward.

I've follow-up on that. You also talked about being more cost efficient versus the competition. Therefore, then how do you drive retention ratio above 15%? How do you drive same-store growth if you're more efficient?

Yes. Our growth and our expansion rates are actually driven by the use cases. So Gen AI is a great example of something that's getting a lot of traction in the marketplace. We see Gen AI is a real tailwind for us from an execution perspective as it opens up new use cases. So I'll give you an example. We have a retailer in Israel that's using a large language model to really transform their retailer experience. So they're actually -- the shopping cart actually talks to the consumer as they're walking around the store. And Teradata actually powers that large language model for that company. All the feature engineering is done in Teradata Vantage. They actually use AWS SageMaker to train the model and then the scoring of the model to actually give the recommendation is again done inside Teradata. So it gives a good use case that integrates together the capabilities of Teradata, the capabilities of the hyperscaler utilizing a Gen AI large language model for real business impact. So the growth of use cases, the growth of data that's being accessed is what drives our expansion rate.

I would like to have a dialogue with my shopping cart.

Yes. Can you talk about maybe the unstructured data and whether you guys are able to run queries for unstructured data versus relational data and how that's evolved over time and whether you're under-indexed or on par with industry? Maybe just talk about that.

Yes. I'll give another example. So Volkswagen and Europe actually use real-time streaming data from shop floor robots that streams data into AWS S3 storage, native object store on AWS. And we actually have Teradata query engines and analytics engines sitting next to that data processing that data in real time to actually make a recommendation to the shop floor robot on whether it has to redo the weld on that manufacturing line. And so utilizing real-time streaming is just one example of different kinds of data sets that the Teradata platform is opening up to over time. We have other examples of -- we have a retailer of restaurant chain, actually, that utilizes Teradata to process video data to actually make recommendations about how the kitchen should operate. So lots of different examples of different types of data, and that's one of the things that we've done from the company's perspective. So when I talk about having a data platform, what I mean from a platform perspective is that we open up the Teradata engines for query processing and analytics to as much data as possible. And so we use partnerships with organizations, like Starburst, to access lots of different data sources. We have lots of built-in integrations in the platform to access different data sources and again, it goes to the whole strategy of to drive expansion into the future, opening up as much data as possible structured and unstructured will be really powerful as we move forward.

I think we're out of time. 20 seconds is probably not enough for me to ask a question and for you to answer. So thank you so much for the insights. Thank you.

Thank you. Thanks. Thank you very much.