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.

clear all ✕

why aren't all 4 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

Assertion Not checkable as stated
Housley: Moving from Hadoop to cloud data stacks has been very tough
“One of the things, one of the transitions that Joe and I went through, which I think a lot of people in this room went through, was the transition from the Hadoop world, from the previous big data world, into this new, like, cloud-based data engineering snack,…”
Matt Housley Oct 24, 2022 ▶ 1:03 Fundamentals of Data Engineering | Joe Reis and Matt Housley
Insight
Housley: Core data engineering issues haven't changed in 20 years
“A lot of the core issues in data engineering actually haven't changed that much in 20 years, and so people got so excited about technology in the transition in the 2000, the internet bubble, rise of Google, the rise of Facebook, that they lost sight of that”
Matt Housley Oct 24, 2022 ▶ 4:39 Fundamentals of Data Engineering | Joe Reis and Matt Housley
Insight
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.”
Matt Housley Oct 24, 2022 ▶ 6:55 Fundamentals of Data Engineering | Joe Reis and Matt Housley
Insight
Housley: Statistics and ML skills cannot overcome poor data inputs
“No matter how good you are at statistics or machine learning, it's hard to make sense of data without having some quality inputs.”
Matt Housley Oct 24, 2022 ▶ 12:07 Fundamentals of Data Engineering | Joe Reis and Matt Housley
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