ETL
topic on 4 shows · 10 statements across 10 episodes
In Depth 
Latent Space 
the MAD Podcast 
the a16z Podcast
10 statements about ETL, every show
Borgman: Data architectures are shifting from batch ETL to Kafka streaming
“And that's an architecture I would say that we're seeing a lot of out there is Kafka as opposed to more traditional batch-oriented ETL.”
Handy: Early cloud data startups ignored the transformation stage of ETL
“No one had taken seriously the T part of it, the transformation part of it.”
Goyal: Matching runtime and eval abstractions eliminates the AI data ETL problem
“If you structure your code so that the same function abstraction that you define to evaluate on equals equals the abstraction that you actually use to run your application, then when you log your application itself, you actually log it in exactly the right for…”
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…”
Turck: Companies with $100M+ ARR have been built solely on data connectors
“There's like this whole world of ETL or ELT companies on the one hand, and then orchestration companies, and all of those are you know, the entire companies, a hundred million plus ARR companies are being built. Solely on building those connectors.”
Reis: Data engineering paradigm is swinging back from ELT to ETL
“But what's interesting right now is the discussion is actually moving back to ETL. I, I'm starting to see more and more discussions about how ELT is a bad paradigm, and again, remember when I said talk about pendulums? The pendulum again is swinging back to ET…”
Naous: All enterprise data stack layers must be redone for operational analytics
“Every single layer will need to refocus on being operational, immediate, and self-service. So ETL, storage, processing, analytics, access, and presentation, all those layers are going to need to be redone in order to get to operational analytics.”
Naus: ETL modernization is difficult due to domain specificity and manual integration
“I think two reasons why ETL has been so hard. The first one is it actually requires domain specificity. Like, ETL for healthcare is not going to look the same as, ah, ETL for financials. For ride sharing or whatever, like the ontologies, the things that they c…”
Snowflake will strictly focus on data warehousing over ETL or BI
“We see ourselves staying very close to home. I think when we think about what can be done with the data warehouse We don't have to become, think about ETL or ELT, nor do we have to think about BI and advanced analytics to do really meaningful things to drive o…”
Ribant: Datorama mostly competes against fragmented, multi-tool traditional BI stacks
“Mostly what we see in terms of competition is, if you remember the slide where I had the whole process with the, all the different pieces, an ETL tool, a database, et cetera. That is mostly the competitive set that we, ah, that we see.”