Snowflake

“We spent two years, you know, making Making Python non-porous. And it was an enormous effort to do that.”

“Don't be afraid, you know, that people will react poorly to it. They won't. The good people will actually love it. And especially if you're in the leadership role and who isn't, you know, this is really what people want. They want to inject energy and focus an…”

“In a world of AI, if you don't have highly organized, optimized, sanctioned, and trusted data, what do you want, you know, your models to do? Just kind of train on, on, on a data lake. I call it a landfill. You know, I mean, you have no idea what the hell is i…”

“Nine out of 10 conversations I have with customers are not technology and architecture and all that and migrations. It's about industry use cases.”

“I think that there still will be a future for BI companies, business intelligence, sort of, Tableau's, Looker's World. And, you know, dashboarding is done for a number of reasons. Sometimes it's just, you know, basically providing data in the consumable format…”

“Federal is, is, is a very small part Of our business, because we spent, we're in the process for years and years and years to meet those standards.”

“If you're in a SaaS subscription model, they got to wait for their next drill before they can start cutting off a limp here. Whereas with us, you can do it in near real time. Investors don't like it. I understand because they love it on the way up. They just h…”

“We don't think, you know, you can have a data cloud in a single public, on a single public cloud platform. By definition, you can't, right?”

“Historically a database was just, you know, a platform that was self-contained and it had standard interfaces like ODBC and JDBC that you, that the application used to access the data. Now it's like, well, wait a second, you know, we don't want to operate that…”

“I have an allergic reaction every time I hear data warehousing, because To me, it's just a type of workload now. It's no longer a market.”

“Our founders were two French guys, long time, you know, Oracle CTOs, technologists architects. They were really responsible for making Oracle from the departmental level. You probably can't remember that far back, but Oracle at one point in time was a departme…”

“Culture shorts and sifts. You attract the right ones and you start losing the wrong ones. So it's actually quite perfect. If people are leaving, they're just not your DNA. They're not your blood type.”

“We don't do layoffs because we don't wait until there is a, you know, huge headwind. We're always pruning the tree, so to speak, right? So we don't have to do it as some massive event that is super unsettling.”

“For ad hoc, you know, nothing is going to be better than the natural language. I, at least I'm already using it. You know, we push Salesforce data into what we call Snowhouse. That's our internal Snowflake database.”

“I did diligence on snowflakes B and told whoever asked me to pass. Cause I'm like redshift exists. Like AWS is not asleep at the wheel.”

“I think you look at like Databricks versus Snowflake and it seems like Databricks has had some advantages by not being public you know, in, in that fight.”

“On the other hand, it's absurd if we think we are SAP or Salesforce. We are not. There are, you know, somebody managing a hundred billion dollar supply chain ecosystem with a complicated software provider isn't saying, hey, I'm going to use SI and I don't need…”

“A data platform that especially spans CSPs has the right, you have to earn it, has the right to be as large as a CSP itself.”

“I think what happened was the company was a little slow to reacting to changes from things like machine learning and AI. And that was a little bit of, honestly, the reason why Frank voluntarily pushed for the change, because he felt presently that we are heade…”

“We need to think of AI the same way we think about software engineering, which is there's a right and there's a wrong. It cannot be this mode of like, YOLO, AI, you can get some good answers, some terrible answers, it's your problem. And so we very much emphas…”

“Among the earliest places where this went to work was in our relationship with Microsoft, which was okay, but not that great because they had a one P relationship with Databricks. And they're always kind of conflicted about is fabric the answer or snowflake th…”

“The great companies of this century, a company like a Google or a Meta, were more data-first companies than like purely product-first companies than pretty much any others compared to before.”

“Early last year, we actually went down the path of creating foundation models. We created a credible MOE model. This was early last year, but we also quickly realized that our ability to compete with the likes of OpenAI or Anthropic was going to be really hard…”

“Snowflake had basically specialized at every layer possible, and there was a very long distance between the engineer that did a feature and the customer that made use of the feature, and there were like seven to 10 layers of teams that were involved.”

“We've rolled out coding agents to all of our solution engineers, and they are excited because that just dramatically lowered the amount of time it takes to create a demo.”