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.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

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.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

The Netflix TechBlog

MARCH 2, 2021

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

Analytics C++ Innovation Engineering 207

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.

Network 150

Network Tuning AWS Big Data 150

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.,

Cloud 137

Cloud Big Data AWS Analytics 137

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.

Analytics 152

Analytics Availability Media Social Media 152