Data Mesh

“At this point in time, it looks like a Frankenstein creation because we have to stitch together a lot of technologies that exist and they weren't designed for this model of reconfiguring, you know, being reconfigured in this way.”

“The data can be only immutable if we build two time timestamps into every single kind of representation of the data, and those two timestamps are when something actually happened, and when we process that information, our understanding of that data.”

“So we will publish that open source. We'll have an open source reference implementation. So we're working on it internally.”

“Centralization of the data, centralization of the organization, functional division between the data and non-data, those are the things that have led to kind of a system that is fragile to scale and change at the macro level, not at the bits and bytes level, r…”

“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.”

“I guess, ah, seems hard to manage and practice. The way I've seen people describe it is basically it's the thing that you naturally create when you're a very big organization and you can't have a centralized data team that can possibly centralize everything, w…”

“The piece we didn't bring from the data mesh was the notion of federated query. Because the problem with federated query is the latency of the query is the worst performing member of the federated group. Right? And so we still have a centralized data repositor…”

“I think the lasting legacy, ah, of that, though, is this concept of data products, creating these sort of curated data sets from data that can live in, in multiple places, and thinking about them from a product perspective, with a product mindset, which is to …”