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1. Streamlining Membership Data Engineering at Netflix with Psyberg

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. What is late-arriving data? Let’s dive in!

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Analytics at Netflix: Who we are and what we do

The Netflix TechBlog

But there is far less agreement on what that term “data analytics” actually means?—?or Even within Netflix, we have many groups that do some form of data analysis, including business strategy and consumer insights. or what to call the people responsible for the work.

Analytics 240
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Formulating ‘Out of Memory Kill’ Prediction on the Netflix App as a Machine Learning Problem

The Netflix TechBlog

More importantly, the low resource availability or “out of memory” scenario is one of the common reasons for crashes/kills. We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform.

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Data pipeline asset management with Dataflow

The Netflix TechBlog

Let’s define some requirements that we are interested in delivering to the Netflix data engineers or anyone who would like to schedule a workflow with some external assets in it. The answers to these questions is something we would like to address in this article and propose a clean solution to this problem.

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Optimizing data warehouse storage

The Netflix TechBlog

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203
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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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Friends don't let friends build data pipelines

Abhishek Tiwari

Data Pipeline A data pipeline is a software that ingests data from multiple sources, transforms it and finally makes it available to internal or external products. Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Depending on frameworks, data processing units (a.k.a

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