Data Lake
topic on 6 shows · 11 statements across 10 episodes
We Live to Build 
the Neon Show 
No Priors 
the MAD Podcast 
the a16z Podcast 
20VC
11 statements about Data Lake, every show
Ghosh: Semi-Structured and Unstructured Data Lakes Will Become Massive
“I think data lakes will see more and more semi and unstructured data because you can squeeze more enterprise value out of them, which has not been true. So infrastructure around semi and unstructured data lakes One of our companies, Aaron is working in that do…”
Borgman: Enterprises will never store all data in a single repository
“We do think data lakes are where you're going to want to store as much data as you can, just because the economics will drive that, but you'll never store everything”
Peng: Differentiation fails if customers cannot repeat it in one sentence
“But I think differentiation in the customer's voice. It's one thing for you to be able to say why your data lake is better than the others, but if your customer can't parrot that back to you in one sentence, then you haven't done your job yet.”
Tom Pierce: Data Lakes Shift Data Filtering Burdens to Downstream Consumers
“The task of filtering the water to make it drinkable has been shifted away from the data collector, because he just put it in the data lake, drink at your own risk, and when you come, you know, dip your bucket into the well of the data lake, you need to make s…”
Slootman: Data lakes are 'landfills'; AI requires highly organized, sanctioned data
“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…”
Housley: Many big data era data lakes turned into data swamps
“In many cases, I mean, I, I've worked in companies like this, it just turned into a data swamp, and that's because, in spite of the amazing technology we had, we kind of lost sight of these fundamental things.”
Dehghani: The debate between data warehouses and lakes is irrelevant
“And I think this kind of funny war between warehouse and lake and web model We should access the data that that seems to me a little bit irrelevant because both of those access models are very acceptable.”
Dehghani: Enterprise data lake migration should start with data consumer needs
“I think you start going backward from your consumers of the data data lakes. So look at who's accessing it, why they're accessing it, what data do they need? Work backward and go back to the source.”
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…”
Dhillon: Enterprise data architecture is shifting from data warehouses to data lakes
“What we're seeing is a trend away from legacy data warehouses into data lakes, which are then consumed both by people using modern visualization products, like say a Tableau, and also by lots and lots of data scientists”