Fivetran

“So marketing data is often like the initial use case for Fivetran at a large company.”

“The additional cost of compute and storage to replicate the extra data, to do those steps, those transformation steps inside the warehouse Are so small now, you know, they're less than what it's going to cost you to pay your data engineer for a week to build y…”

“And this is different than how it's historically been done, but the big advantage of Doing MDM and other similar things in this way is that it's non-destructive. So you still have the original data. If you make a mistake and you realize later, oh, I said these…”

“If the data source is really large, it's something that's just yours, so Fivetran's never going to build a connector to it, and it's relatively stable, like it's not constantly changing configuration, then you can build your own data pipeline using the tools p…”

“And we're working on we're working on publishing more about, like, what do you need to do to make an API that's friendly to replication for data warehousing? Whether it's by us or one of our competitors or just the customers building their own data pipelines, …”

“And then sometimes they actually change the APIs for us.”

“And the really critical thing we did that laid the foundation for our eventual success was that we said that it was our responsibility to make the data match. Which is actually unusual in the field of data integration. Most data integration tools, they see the…”

“We have customers who run billing out of their data warehouse.”

“And is actually as far as I know, one of those, like, companies are over a hundred million in, in, in revenue.”

“You know, it doesn't undercut everything for Fivetran, but it potentially undercuts the big sources, which I imagine are the things that are, like, the real drivers of revenue for them.”

“My read is that people like us, people like Fivetran, while we are critical to their success as platforms, because we drive a ton of consumption. They don't actually really care about the dollars that we make as businesses. Cause they're so tiny relative to th…”

“And so that means that companies like us and companies like Fivetran that are big parts of that, you know, we're not going anywhere.”

“When people started using the term modern data stack, there was a there, like fivetran, dbt, mode, looker, et cetera. These are tools that. Were built around an idea of how data technology should work. And it was a, it was, and is a good idea.”