And scoring those models once they’re – once they’ve been developed to put them into production is something that we’re super strong in. And with the addition of Stemma from that data discovery and data lineage perspective, it has given us even more capabilities in that area.
Nehal Chokshi: Great. Could you discuss who do you see as the primary competitors of Stemma?
Steve McMillan: I’m sorry, could you ask that question again? I didn’t quite catch it.
Nehal Chokshi: Who are the primary competitors of the Stemma acquisition?
Steve McMillan: Yes. We saw Stemma is pretty uniquely placed in the marketplace in terms of the offering that they’re developing and the capability that they’ve got in the marketplace, and we saw it as a great add to the team. Certainly, they’re not in the data catalog area, but they are – they have got a number of different capabilities that ensures that organizations have the best possible data to feed into their analytical models and analytics platform.
Operator: Thank you. The next question will be from the line of Derrick Wood with TD Cowen. Your line is now open.
Derrick Wood: Great. Thanks for taking my questions. I wanted to ask about how you’re thinking about go-to-market strategies between selling a Cloud Data Warehouse and a Data Lake, if you will. I mean we’ve seen some vendors that take approach, an approach of really selling two different platforms, different buying motions, different buyers, different use cases. Others have taken more of a kind of single centralized approach and maybe running different underlying data stores, but all on one platform. What is your — and Data Lake is fairly new for you guys, but what is your kind of longer-term strategic approach at addressing both these types of environments?
Steve McMillan: Yes. Our philosophy is different to our competition from this perspective. We believe that our platform can service all three of those different choices. And we really do look at it as a deployment choice. So whether a customer wants to deploy a data warehouse in the cloud, a Data Lake in the cloud or Data Lake House in the cloud, our underlying technology will enable all three of those models and enable our customers to utilize data that’s stored in any one of those data deployment models and the cloud and integrate that data together better than any of our competition can. So the recent announcement in terms of VantageCloud Lake, which we just announced on the Microsoft platform at the start of June, extend our capability to have that Lake and Lake house deployment in the Azure ecosystem and obviously, building on our industry-leading cloud data warehouse capabilities.
The ability to integrate all those together and take away the choice that our customers may have to have in terms of select multiple technologies to service that is something that we think is differentiating in the marketplace, Derrick.
Derrick Wood: Steve, thanks for that. Sorry, I got on late, but – so sorry if this has been asked. But Claire, I know you guys don’t have the same kind of optimization dynamics and headwinds that we’ve heard from kind of pure consumption-based models in the cloud. But just curious to get an update on spending behavior, the macro, how it’s – how it feels like it’s changed over the last three to six months and whether generative AI discussions have started to become any workload movers yet or that’s still too early.
Claire Bramley: Yes, sure. Thanks very much. So yes, what we’re seeing is good strength in our expansion business. So we mentioned earlier in the call that seeing strong performance expansion both in the cloud but also on-prem. That’s reflected in our net expansion rate, but we’re also seeing strong expansions at the point of migration. So I think that comes back to you the confidence that our customers have in our platform. They’re not wanting to take risk, the fact that they have mission-critical workloads that they want to maintain on the Teradata Vantage platform. So very happy with those dynamics and the conversations that we’ve been having with customers, and that’s what gives us the strong pipeline as we look forward to the second half of the year.
