The Netflix TechBlog

NOVEMBER 14, 2023

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. Some techniques we used were: 1.

Data Engineering 264

Data Engineering Engineering Processing Games 264

Dynatrace

JULY 6, 2022

And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues? This requires significant data engineering efforts, as well as work to build machine-learning models. Creating a sound IT automation strategy. So, what is IT automation? What is IT automation?

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Artificial Intelligence Tuning Strategy Big Data 191

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

SEPTEMBER 18, 2020

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 240

Analytics Engineering Data Engineering Tuning 240

The Netflix TechBlog

OCTOBER 30, 2020

Part of our series on who works in Analytics at Netflix?—?and I’m a Senior Analytics Engineer on the Content and Marketing Analytics Research team. We partner closely with the business strategy team to provide as much information as we can to our content executives, so that? and a Swiss army knife ???: Why Netflix?

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Analytics Engineering Innovation Metrics 136

Abhishek Tiwari

JULY 12, 2018

Building data pipelines can offer strategic advantages to the business. It can be used to power new analytics, insight, and product features. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

NOVEMBER 20, 2023

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Processing 210

Processing Big Data Efficiency Engineering 210