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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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.
Data: Fast Data Our main data lake is hosted on S3, organized as Apache Iceberg tables. For ETL and other heavy lifting of data, we mainly rely on Apache Spark. In addition to Spark, we want to support last-mile dataprocessing in Python, addressing use cases such as feature transformations, batch inference, and training.
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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.
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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.
Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users.
Data is a tool that enhances decision-making, complementing the deep expertise and industry knowledge of our creative professionals. Although there was already a process for creating and comparing budgets for new productions against similar past projects, it was highly manual.
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