The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 51 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
dbt CEO Tristan Handy: The modern data stack concept is dead
“I don't think the modern data stack is a useful idea anymore.”
Handy: Hyperscalers build features for RFPs, not to kill independent tools
“When you talk to the folks at the hyperscalers, they will say, we are, we're like making sure that our solution is like covers all these different areas, but it's mostly not. Because we want to compete in these areas. It's mostly because people come to us with…”
Handy: Building in-house is often faster than M&A for data infrastructure
“Had to build, you know, there's like the iceberg, which is 10% above the water and you can see it. And then there's 90% below the water for a data company. The platform is the below the water part. And then the functionality that you build on that platform is …”
Tristan Handy: Software multiple expansion has shifted from modern data stack to AI
“If what you were trying to do is maximize the multiple that your software company was trading at, then AI is the enemy because all the multiple expansion has moved from modern data stack to AI.”
Handy: Social media pricing backlash did not cause mass dbt cancellations
“Our business as a result has not really had a hiccup. But if you only existed on Twitter or LinkedIn you would think that you know, our customers desired us on mass and we're every single one of them was livid and canceled, but that just like didn't happen.”
Handy: Early-stage VCs doubted data practitioners would learn Git in 2016
“Early stage VCs that I spoke to back in 2016 told me that, like, it wasn't at all clear that data practitioners actually wanted to learn Git.”
Handy: Data processing will be polyglot with non-SQL abstractions within five years
“We really do think that the future of data processing is polyglot, and I think that if you look in five years, you will find more robust abstractions on top of data, and even in the DBT ecosystem, than SQL.”
Handy: The core modern data stack architecture remains a good idea
“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.”
Handy: CDOs shouldn't build data platforms by integrating nine point products
“If you say I want a modern data platform as a CDO, like the right answer is not go out and buy nine different products and integrate them together.”
Handy: Cloud platforms care about compute consumption, not partner revenue
“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…”
Handy: Reverse ETL tool value accrues to sales/marketing, not data teams
“It turns out that the value of a reverse ETL tool does not accrue to the central data team. It accrues primarily to. Sales and marketing teams who get the data.”
Handy: dbt will start exploring visual, GUI-based workflows this year
“And so this year will probably be the year where we start playing around in that space.”
Handy: Low-code data tools must read and write underlying code
“You have to get no code, low code experiences that read and write code so that code can go through a get PR process and it can have all the same mature stuff built on top of it as any other code.”
Handy: dbt Labs aims to power ecosystem infrastructure, not own cataloging
“As we move forward, we're not looking to, like, own cataloging or own whatever, these different categories. We're looking to be the infrastructure that powers this ecosystem, because it turns out that you don't actually want to connect to, like, four different…”
Handy: Depending on data engineering backlogs destroys data analyst productivity
“That is like the death of the data analyst as like a productive member of your team. They will get frustrated. They will leave. They, they're, they don't have great career paths. All of these like negative outcomes.”
Handy: Data analysts spend 50% of their time blocked by engineering
“Like if you take a team at a like very good, like the data forward organization, a team of 20 data analysts, my guess is that they spend 50% of their time blocked.”
Handy: Batch transformation is not LookML's core focus or innovation
“The part of LookML that does batch based transformation is, is not the primary focus of their product. It's not like the core innovation that they have.”
Handy: Reverse ETL will automate workflows and multiply the data market opportunity
“There's a class of tools that takes the data that is in your data warehouse and pushes it back to operational systems. And I think that you will, as soon as that starts happening, you can automate the entire process and all of these technologies become, you kn…”
Handy: Looker and Mode were superior to pre-cloud Tableau
“I had a strong preference to use tools like mode or looker over a tool like tableau because tableau was pre cloud and it assumed that you were going to be able to download all the data that you needed to operate on into your local cache.”
Handy: Venture capital created too many data startups too quickly
“There was just, there were too many companies created too quickly.”
Handy: The shift from ETL to ELT will remain true forever
“One of the kind of trends inside of this is the transition from ETL, extract, transform, load to ELT, extract, load and transform. And that seems to anyone who's not in data that Might not seem like a big thing, but in fact, it's like a really significant tran…”
Handy: dbt Labs and Fivetran are not going anywhere
“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.”
Handy asked dbt marketing to adopt 'the analytics stack' label
“My big conclusion is I sent an email to our product marketing, our head of product marketing. I was like, Hey, can we just say the analytics stack? Like this is a set of technologies that works together to do analytics. And it kind of tries to get away from th…”
Tristan Handy: Building a production data system is building a software system
“One of the core beliefs about the, that we have about the profession is that data and software are not that different. And when you're building a production data system, you're building a production software system, which means that we should be taking lessons…”
Tristan Handy: The semantic layer centralizes meaning like data platforms centralize data
“The semantic layer in the same way that like a cloud data platform centralizes data, so you can all use the same data. The semantic layer centralizes meaning. How do you actually analyze that data to produce a particular business metric?”
Tristan Handy: dbt replaced almost its entire executive team within one year
“If you look today the only people who are consistent presence on our executive team from a year ago are me and our CFO and everybody else around the table is, is new.”
Handy: dbt Labs closed quarters on 1x pipeline coverage two years ago
“Two years ago, We could walk into a quarter with one X pipeline coverage and you would just, the deals would just show up and that's not how the world works today.”
Tristan Handy: The GitLab handbook will be used for decades
“I'm sure that people will continue to use GitLab for a long time, but I think people will continue to use the GitLab handbook for, like, decades and decades.”
Handy: The original modern data stack was four core layers
“The original modern data stack was four layers. It was data ingestion. How do you get your data from all of your different upstream systems? It was data storage or warehousing, and how do you actually store and compute data? It was transformation. And then it …”
Handy: 100x more people write SQL than Spark or Scala
“There are actually two orders of magnitude more human beings on the planet that can write SQL than can write Spark or Scala or whatever.”
Handy: Data profession is two decades behind software engineering
“And as a profession, like data is generally Probably two decades behind software engineering in terms of, like, the productivity of practitioners and the level of abstraction and everything.”
Handy: Gap between modern data stack and machine learning will vanish by 2027
“Again, if you look in five years, I think that this distinction will have been sanded over and will not be salient anymore.”
Handy defines the modern data stack across four distinct functional layers
“When we talk about the modern data stack, we think about what's really four layers. So there's data ingestion. There's the data warehouse. There's data transformation or like taking all that raw data and like turning it into something valuable. And then there'…”
Handy: Amazon Redshift's launch sparked a rewrite of data stack products
“Those set of technologies have really been completely rebuilt. I think over the past seven years, really, it was like the introduction of Amazon redshift with In, in, in, that sparked kind of a rewrite of all of the products in that space.”
Handy: Data lakes offer more flexibility but require more effort
“Where we are today, the data lake can kind of do anything. But it also probably takes more work to do anything. Whereas the data warehouse is, has a more constrained set of use cases, but it is much easier to get up and running for those constraints set of use…”
Handy: Data transformation has shifted inside data warehouses using SQL
“What's happening now or over the past, you know, five or so years, the, Transformation step now happens inside the data warehouse and it happens in SQL. And because of that, it is now accessible to a dramatically larger number of people.”
Handy: Data analysts learn technology to solve problems without identifying as technologists
“I think that a data analyst is somebody who answers business questions with data and they have a, they frequently will have a business or econ degree. They like are interested in solving business problems, but they're also not afraid of technology and they oft…”
Handy: dbt's philosophy empowers data analysts to think like software engineers
“Yes, that is completely true.”
Handy: Data engineers should focus on scalability, not business logic
“Data engineers shouldn't want to be spending their days expressing business logic. Like how do you amortize revenue across multiple periods? They are technologists. They should want to be thinking about platforms and scalability and all of these like hard tech…”
Handy: Once sensitive data lands in a warehouse, it resists elimination
“If you land data in your warehouse, it is very hard to ever have it go away completely.”
Handy: Turnkey solutions for in-flight data masking did not exist in 2020
“The easy solution to this, I don't think by and large exists yet.”
Handy: CI/CD guardrails enable both software democratization and governance
“What you do is you have mature CICD processes. You have like DevOps workflows that, so you like build these guardrails that create high quality processes around code releases to production where you have your cake and eat it too. You have democratization. You …”
dbt Labs has internal prototypes for AI-generated models, tests, and documentation
“We've already got internal prototypes working of generate me a model that does this or generate me tests for this model or you know, write documentation for, so we've got all of this stuff that is going to be making its way through at some point.”
Tristan Handy: dbt had 1,000 company users before raising venture capital
“We waited, waited a long time to raise any venture funding at all. We had a thousand companies using the product before we raised a single cent.”
Handy: Data teams in 2016 shared SQL files as email attachments
“Back in 2016, the, like, data practitioners were sending each other SQL files as attachments to emails, and that was, like, the way that we worked together.”
Handy: dbt serves batch data workloads, not sub-100ms real-time applications
“There's a lot of data science that's done Internally where like you're doing predictive analysis that, you know, the data latency can be a day or it can be like last quarter's data is fine. And those data science workloads are often run on the exact same stack…”