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Our First Netflix Data Engineering Summit

The Netflix TechBlog

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

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What is IT automation?

Dynatrace

And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues? This requires significant data engineering efforts, as well as work to build machine-learning models. Creating a sound IT automation strategy. So, what is IT automation? What is IT automation?

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Scaling Appsec at Netflix (Part 2)

The Netflix TechBlog

By Astha Singhal , Lakshmi Sudheer , Julia Knecht The Application Security teams at Netflix are responsible for securing the software footprint that we create to run the Netflix product, the Netflix studio, and the business. Our customers are product and engineering teams at Netflix that build these software services and platforms.

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Formulating ‘Out of Memory Kill’ Prediction on the Netflix App as a Machine Learning Problem

The Netflix TechBlog

Since memory management is not something one usually associates with classification problems, this blog focuses on formulating the problem as an ML problem and the data engineering that goes along with it. for us at Netflix, this is a combination of the device type, app session ID and software development kit version (SDK version).

Big Data 179
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A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix

The Netflix TechBlog

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 data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207
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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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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?