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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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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

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Reimagining Experimentation Analysis at Netflix

The Netflix TechBlog

Our A/B tests range across UI, algorithms, messaging, marketing, operations, and infrastructure changes. Due to compression and high performance computing, scientists can analyze billions of rows of raw data on their laptops using languages and statistical libraries they are familiar with like Python and R.

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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

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 Data Engineer at Netflix?

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Ready-to-go sample data pipelines with Dataflow

The Netflix TechBlog

The main workflow definition file holds the logic of a single run, in this case one day-worth of data. This logic consists of the following parts: DDL code, table metadata information, data transformation and a few audit steps. It’s designed to run for a single date, and meant to be called from the daily or backfill workflows.

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5 key areas for tech leaders to watch in 2020

O'Reilly

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Also: infrastructure and operations is trending up, while DevOps is trending down.

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

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.

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