Databricks

“We thought there was one example of a good one, which was Red Hat, but there weren't many other examples that were doing well, and now we've seen Red Hat, you know, also, you know, did not survive as an independent company.”

“From early on, we said, look technology comes and goes. Spark in 10 years will have probably aged and hopefully we'll come up with other innovations, so let's pick a name that separates the company from the open source technology, and hopefully we can continue…”

“I think the SAS model applied to open source is gonna be really disruptive. And, you know, so people, because of this transition period, we had these on-prem open source vendors. People think maybe open source won't work in the future in the cloud, but I think…”

“We actually have thirty million downloads of these projects just alone every month.”

“If you, if you're doing open source development within your company, you can attract much better engineers, because you can tell them, Come here, work here. You can work on these projects, and you can put these on your CV, and when your next employer asks you …”

“They don't want to talk openly about it, but most of those vaccine teams behind the scenes built basically what we call the lake house. We stole all your data, store all your data and do AI on it. And it was really used for these sort of vaccine development bo…”

“So when you publish your pricing like this, you are subjecting it to competitive analysis by others. So it's not like you could just dream up these numbers. You have to be able to justify them to a customer who will come back and say, But this other vendor cha…”

“And as you can see, it's very disproportionately time spent on new prospects. and that is completely okay with me because for us to grow a hundred percent year over year, we're constantly adding new customers to our account base. 30% with customers, right? We…”

“And we will definitely do a deal review for every deal that has been committed by the account executive. That's them saying this deal is going to come in. So we'll inspect that and make sure that they have the full team behind them.”

“Over the last four and a half years, I've been working on growing our team by a hundred percent year over year.”

“What is, I think, special is that we're very data-driven around it, and we own what it is that we're putting into the scorecard... Different people on the panel are given very specific characteristics to dive into and to really understand at a deeper and deepe…”

“We're doing a change in our business, moving from focusing on signed contracts to what is going on on the customer's usage of the platform or their consumption.”

“I'll give an example of something that has modified over the last couple of years, and that is really around big data selling experience. You know, a couple years ago, you had to already know the ecosystem in order to be good at it, but as we've grown as a com…”

“We use outreach and gong in our tech stack. And then we're also scraping calendar data to make sure that we're really as accountable as we can be to how account executives are spending their time.”

“We actually inspect our pipeline coverage ratios every week, and we are working to if we're hitting the target, that's great. If we're above the target, that's a strong indicator that there's going to be over success. And if there's a gap, we often will do a s…”

“And then at the beginning of COVID, we decided to change the whole company. We said we're not going to value that anymore. We want to be more customer obsessed. And so we pivoted the entire company to a consumption model.”

“All of the companies I've worked at, VMware, Amazon Web Services, and now I hope Databricks, they would have been successful with or without me. There was an inevitability. Customers were going to virtualize their data centers. People were going to consume tec…”

“In our case, that principle is, we look for long-term company builders. We look for other people who've been five, six, seven, eight years, and been promoted and built other companies. And longevity matters a lot.”

“We've hired a 175 marketers on from almost a very tiny team in the last six years. And there were some years where we had to hire like 40 to 50 people on a base of 20 or 25.”

“I would say our SAs tend to be very technical. A lot of them can code, they can do POCs, they can do pilots. They're not just doing demos. And we expect our salespeople to understand the technology, not just be able to bring in the right resources.”

“I do think your inside sales team should be together. I like the bullpen concept. I think they need to learn from each other. They need to feel the energy from each other”

“We were trying to sell to all the smartest Silicon Valley tech companies, which is actually pretty hard. A lot of those folks like to build their own stuff, right? They're early adopters of tech, but they're also like harder to get big dollars out of early in …”

“I think probably in the first quarter, I probably hired 40 sales folks because I saw the kind of demand that I thought, and we had some big revenue aspirations, but we built both.”

“And also our baseline continues to grow. So as people get more and more data and more and more queries, our revenue grows as well. Right. Which I think is a way superior model than a licensing or Seat based. Cause eventually you might run out of users. For us …”

“Ron joined Databricks as CRO when there was less than a million dollars of ARR.”

“And if I had to give myself advice would have been invest even more early when you, I think we could have grew even faster.”

“I think in general, if you have a really technical product, most of the buyers, if they're technical buyers, they want, they don't really love talking with salespeople. So you have to add a lot of value on the technical front. You need to know your stuff. They…”

“And A-sixteen Z, they have a lot of those kind of go to market motions where they'll set up basically a forum for you to present to large enterprises. I know not everybody has maybe a VC backer, but those programs are incredibly valuable. Sometimes people like…”

“You never want to do, do like a one-off, but if you hear something from 20 different customers, put it in the product, right?”

“Whether it's Databricks or Snowflake, whether it's Shopify, whether it's BigQuery, whether it's All S three, all the places where you're storing data through your company, all of that needs to be one consistent data layer for that agent to be able to really be…”

“SpaceX, Anthropic, OpenAI, we'll add in Databricks, we'll have Arsan, one of the co-founders here in about half an hour after this. That's going to create more market value, more value, and more wealth than every other IPO since 2000.”

“I think any industry that is highly valuable, that has a monopoly today, Will not have a monopoly, 12 to 24 months from now, because.”

“You know, still how many of them actually properly adopted AI in the way of coding tools or like systems is pretty nascent.”

“But now you can send LLMs in because the beauty of code is self descriptive. It goes in, it understands what everything is doing and why, and then it can also very easily convert it. And then the key is like, how do you write harnesses to do validation and rec…”

“And so now we have this other problem, which is happening where everybody's like, okay, all my employees are token maxing. My spend on tokens is going up, but I have no idea what I'm getting out for it.”

“We just had a, that car manufacturer just loaded on an extra 70,000 users. They all are going and asking their own questions of it, right?”

“Five point something in billion re-accelerating at 50 or 60% growth.”

“The urgency of I need to kind of get my data state in order and governance around it and context has gone through the roof because people realize without that, they can't actually get AI to work in any meaningful way.”

“Databricks is hiring as at 10,000 people is hiring as many entry-level folks as it ever has.”