21–30 of 108 posts
I guess in their world they’d add a new model for whatever they want to change and then phase out use of the old one before removing it.
For all the benefits, there is a large problem with this approach that often goes unacknowledged. It is fundamentally a business problem, rather than a technical problem, but it has impact on development speed, so it's secondarily a technical problem. The business contract with a consolidated data definition is that everyone in the business, no matter which domain, can rely on it. But think about the red tape that in…
> ... RDF ... SPARQL ... OWL ... I want to believe. (really! I think that's hugely underestimated tech).
It's 2005 again! These tools were pretty cool and an enormous amount of work was put into them. The ontologies were extremely extensible. There just wasn't enough of an ecosystem putting them into practice and demonstrating their utility. Their examples are nice: https://github.com/Netflix-Skunkworks/uda/blob/9627a97fcd972...
Imagine trying to convey this example in RDF/XML (that's more like 2005).
RDFa and microdata stuff for sharing got pretty far, but those are often simpler vocabularies (at least when seen from the outside, maybe folks who index that shit has something nicer going on, idk).
Honestly, I feel kind of relieved seen Netflix using this stuff. I suggested using this kind of tech to model knowledge in systems that had this problem of knowledge representation several times, but always had a hard time when people said "if it's so good, why no big player uses it?".
For all the benefits, there is a large problem with this approach that often goes unacknowledged. It is fundamentally a business problem, rather than a technical problem, but it has impact on development speed, so it's secondarily a technical problem. The business contract with a consolidated data definition is that everyone in the business, no matter which domain, can rely on it. But think about the red tape that in…
Unfortunately it came about at exactly the same time as NoSQL and Big Data, which are basically the opposite. They let you be really loose with your model, and if some data gets lost or misunderstood, hey, no biggie. It's easier to patch it later than to develop a strong model to start with.
But am I bitter about it? No, why do you ask? Twitch, twitch.
I really believe a common vocabulary makes sense. But it is hard, very hard as you spread across organization (some to be bought and integrated), business processes and time. As soon as it comes to generating stuff things become hard. One may be able to generate interfaces between two systems but which enterprise has only two layers? Yes, if all knowledge is captured in the central catalog we may be able to do it but…
Wikidata? 1.65 billion graph nodes and counting under a common vocabulary.
I feel the dream. But we went to that place 25 years ago, and we saw that it was stupid.
Tell you what, I'll do a raffle. Leave a comment telling me that I just don't get it. One lucky winner will get my copy of this book https://www.amazon.com/Unified-Modeling-Language-Addison-Wes.... You pay shipping.
For all the benefits, there is a large problem with this approach that often goes unacknowledged. It is fundamentally a business problem, rather than a technical problem, but it has impact on development speed, so it's secondarily a technical problem. The business contract with a consolidated data definition is that everyone in the business, no matter which domain, can rely on it. But think about the red tape that in…
It’s a classic pattern in public sector applications, where it’s partially deliberate.
Doesn't Google achieve the same result with Protobuf?