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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.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

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Automated Testing in Data Engineering: An Imperative for Quality and Efficiency

DZone

This holds true for the critical field of data engineering as well. As organizations gather and process astronomical volumes of data, manual testing is no longer feasible or reliable. This comprehensive guide takes an in-depth look at automated testing in the data engineering domain.

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Introducing Impressions at Netflix

The Netflix TechBlog

Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. Collecting raw impression events Filtering & Enriching Raw Impressions Once the raw impression events are queued, a stateless Apache Flink job takes charge, meticulously processing this data.

Tuning 166
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Analytics at Netflix: Who we are and what we do

The Netflix TechBlog

Analytics at Netflix: Who We Are and What We Do An Introduction to Analytics and Visualization Engineering at Netflix by Molly Jackman & Meghana Reddy Explained: Season 1 (Photo Credit: Netflix) Across nearly every industry, there is recognition that data analytics is key to driving informed business decision-making.

Analytics 243
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Ready-to-go sample data pipelines with Dataflow

The Netflix TechBlog

Optionally, this step can use the Write-Audit-Publish pattern to ensure that data is correct before it is made available to the rest of the company. A large number of our data users employ SparkSQL, pyspark, and Scala. some_db.source_table.yaml ??? sparksql_write.sql ??? test_sparksql_write.py agg(F.sum($"view_hours").as("view_hours"))

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. In the Efficiency space, our data teams focus on transparency and optimization.