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DataEngineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “DataEngineers of Netflix” series, where our very own dataengineers talk about their journeys to DataEngineering @ Netflix. Kevin, what drew you to dataengineering?
A summary of sessions at the first DataEngineering Open Forum at Netflix on April 18th, 2024 The DataEngineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our dataengineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. In this talk, we share how Netflix deploys systems to meet its demands, Ceph’s design for high availability, and results from our benchmarking.
At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and dataengineering, we comprise the larger, centralized Data Science and Engineering group.
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. In this talk, we share how Netflix deploys systems to meet its demands, Ceph’s design for high availability, and results from our benchmarking.
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. In this talk, we share how Netflix deploys systems to meet its demands, Ceph’s design for high availability, and results from our benchmarking.
The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.
To directly support great decision-making throughout the company, there are a number of data science teams at Netflix that partner directly with Product Managers, engineering teams, and other business units to design, execute, and learn from experiments. Curious to learn about what it’s like to be a DataEngineer at Netflix?
They require teams of dataengineers to spend months building complex data models and synthesizing the data before they can generate their first report. Finally, their complex user experiences are designed for power users and not suitable for the fast-growing segment of business users.
Dashboard DesignTips Rina Chang , SusieLu What is design, and why does it matter? Often people think design is about how things look, but design is actually about how things work. Everything is designed, because were all making choices about how things work, but not everything is designed well.
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