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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

It is a general-purpose workflow orchestrator that provides a fully managed workflow-as-a-service (WAAS) to the data platform at Netflix. It serves thousands of users, including data scientists, data engineers, machine learning engineers, software engineers, content producers, and business analysts, for various use cases.

Java 202
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Organise your engineering teams around the work by reteaming

Abhishek Tiwari

Over specialisation is considered good in industries such as healthcare and aviation but in software engineering over specialisation can be a blocker. Unlike healthcare and aviation where practices don't change over the decades, software technology is changing every day. Secondly, fine-tune team composition based on work.