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 7 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
Data orchestrators are the central leverage point for organizational data platforms
“We think this like orchestrator is really the central leverage point that makes sense to be the data platform.”
Data orchestrators must be productive developer environments, not just operational tools
“It's critical not to just think of it as a operational tool, but as a place where people can productively work.”
Data teams should focus on computation processes rather than physical datasets
“People think of data sets as physical things, right? Like a table and a database. Right. But in the modern world where you're really applying software engineering processes to data, all that data ends up being computed. And so what we thought really is that yo…”
Data tools should upskill analysts with engineering processes, not replace them
“The way to do this is not to try to remove analysts from the equation. The way to do this is to bring engineering processes into their life and, you know, so-called upskill them.”
Data operations require specialized software engineering rigor and tools
“What really needs to happen in this data space is the software kind of engineering of vacation of data. The acknowledgement that this is not an off outsourceable thing anymore, that this requires software engineering process specialized for the data domain and…”
Data challenges have shifted from compute scale to developer productivity
“An amazing engineering achievement happened in the early, you know, throughout the 2010, which was solving these massive pure technical scale problems. But now we're talking about organizational scale, dealing with complexity and dealing with developer product…”