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
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Dynatrace
JULY 6, 2022
With ever-evolving infrastructure, services, and business objectives, IT teams can’t keep up with routine tasks that require human intervention. This requires significant data engineering efforts, as well as work to build machine-learning models. Big data automation tools. Batch process automation.
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. As with any sustainable engineering design, focusing on simplicity is very important. And excellent logging is needed for debugging purposes and supportability.
The Netflix TechBlog
SEPTEMBER 10, 2019
Our A/B tests range across UI, algorithms, messaging, marketing, operations, and infrastructure changes. Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute. Getting Data with the Metrics Repo 2.
All Things Distributed
NOVEMBER 15, 2016
As I mentioned, we live in a world where massive volumes of data are being generated, every day, from connected devices, websites, mobile apps, and customer applications running on top of AWS infrastructure. Put simply, data is not always readily available and accessible to organizational end users. Enter Amazon QuickSight.
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.,
Expert insights. Personalized for you.
173 
Let's personalize your content