Data Engineering Infrastructure Technology 
The Netflix TechBlog
OCTOBER 28, 2021
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.
The Netflix TechBlog
MARCH 25, 2019
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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The Netflix TechBlog
NOVEMBER 22, 2019
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. Technology advancements in content creation and consumption have also increased its data footprint. Wednesday?—?December
The Netflix TechBlog
DECEMBER 3, 2022
A small but growing contingency of data scientists and analytics engineers use R, backed by the Sparklyr interface or other data processing tools, like Metaflow. With an understanding that the data landscape and the technologies employed by end-users are not homogenous, Dataflow creates a malleable path toward.
O'Reilly
FEBRUARY 18, 2020
It’s also the data source for our annual usage study, which examines the most-used topics and the top search terms. [1]. This combination of usage and search affords a contextual view that encompasses not only the tools, techniques, and technologies that members are actively using, but also the areas they’re gathering information about.
The Netflix TechBlog
MAY 26, 2020
Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. Requirements There are multiple ways you can solve this problem and many technologies to choose from.
All Things Distributed
OCTOBER 7, 2015
In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,
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