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Alexandre Bertails: The Netflix Unified Data Architecture – Episode 40

Автор: Knowledge Graph Insights

Загружено: 2025-11-03

Просмотров: 69

Описание: Alexandre Bertails

At Netflix, Alexandre Bertails and his team have adopted the RDF standard to capture the meaning in their content in a consistent way and generate consistent representations of it for a variety of internal customers.

The keys to their system are a Unified Data Architecture (UDA) and a domain modeling language, Upper, that let them quickly and efficiently share complex data projections in the formats that their internal engineering customers need.

We talked about:

his work at Netflix on the content engineering team, the internal operation that keeps the rest of the business running
how their search for "one schema to rule them all" and the need for semantic interoperability led to the creation of the Unified Data Architecture (UDA)
the components of Netflix's knowledge graph
Upper, their domain modeling language
their focus on conceptual RDF, resulting in a system that works more like a virtual knowledge graph
his team's decision to "buy RDF" and its standards
the challenges of aligning multiple internal teams on ontology-writing standards and how they led to the creation of UDA
their two main goals in creating their Upper domain modeling language - to keep it as compact as possible and to support federation
the unique nature of Upper and its three essential characteristics - it has to be self-describing, self-referencing, and self-governing
their use of SHACL and its role in Upper
how his background in computer science and formal logic and his discovery of information science brought him to the RDF world and ultimately to his current role
the importance of marketing your work internally and using accessible language to describe it to your stakeholders - for example describing your work as a "domain model" rather than an ontology
UDA's ability to permit the automatic distribution of semantically precise data across their business with one click
how reading the introduction to the original 1999 RDF specification can help prepare you for the LLM/gen AI era

Alexandre's bio
Alexandre Bertails is an engineer in Content Engineering at Netflix, where he leads the design of the Upper metamodel and the semantic foundations for UDA (Unified Data Architecture).
Connect with Alex online

LinkedIn
bertails.org

Resources mentioned in this interview

Model Once, Represent Everywhere: UDA (Unified Data Architecture) at Netflix
Resource Description Framework (RDF) Schema Specification (1999)

Video
Here’s the video version of our conversation:

   • Alexandre Bertails: The Netflix Unified Da...  

Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 40. When you're orchestrating data operations for an enormous enterprise like Netflix, you need all of the automation help you can get. Alex Bertails and his content engineering team have adopted the RDF standard to build a domain modeling and data distribution platform that lets them automatically share semantically precise data across their business, in the variety of formats that their internal engineering customers need, often with just one click.
Interview transcript
Larry:
Hi, everyone. Welcome to episode number 40 of the Knowledge Graph Insights podcast. I am really excited today to welcome to the show, Alex Bertails. Alex is a software engineer at Netflix, where he's done some really interesting work. We'll talk more about that later today. But welcome, Alex, tell the folks a little bit more about what you're up to these days.

Alex:
Hi, everyone. I'm Alex. I'm part of the content engineering side of Netflix. Just to make it more concrete, most people will think about the streaming products, that's not us. We are more on the enterprise side, so essentially the people helping the business being run, so more internal operations. I'm a software engineer. I've been part of the initiative called UDA for a few years now, and we published that blog post a few months ago, and that's what most people want to talk about.

Larry:
Yeah, it's amazing that the excitement about that post and so many people talking about it. But one thing, I think I inferred it from the article, but I don't recall a real explicit statement of the problem you were trying to solve in that. Can you talk a little bit about the business prerogatives that drove you to create UDA?

Alex:
Yeah, totally. There was no UDA, there's no clear problem that we had to solve and really people, won't realize that, but we've been thinking about that point for a very long time. Essentially, on the enterprise side, you have to think about lots of teams having to represent the same business concepts, think about movie actor region, but really hundreds of them really, across different systems. It's not necessarily people not agreeing on what a movie is, although it happens, but it's really what is the movie across a GraphQL service, a data mesh source, an Iceberg table, resulting in duplicating efforts and definitions at the end not aligning. A few years ...

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