The Netflix TechBlog

SEPTEMBER 18, 2020

Part of our series on who works in Analytics at Netflix?—?and and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley.

Analytics 227

Analytics Education Innovation Engineering 227

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Processing 230

Processing Data Engineering Efficiency Analytics 230

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 212

Analytics C++ Innovation Engineering 212

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. Users configure the workflow to read the data in a window (e.g.

Processing 214

Processing Big Data Efficiency Engineering 214

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

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Netflix TechBlog

JANUARY 11, 2022

Curious to learn more about other Data Science and Engineering functions at Netflix? To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham.

Innovation 245

Innovation Metrics Engineering Testing 245

The Netflix TechBlog

JANUARY 6, 2025

This article is the last in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Its easier to develop and maintain, and tends to be more familiar for analytics engineers, data scientists, and data engineers.

Analytics 199

Analytics Engineering Cache Entertainment 199

Adrian Cockcroft

FEBRUARY 13, 2023

STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions. AWS Inferentia 2.6x shorter training time, saving 54% energy and 75% cost. Good example, well presented interesting new material.

AWS 64

AWS Energy Architecture Programming 64

The Netflix TechBlog

DECEMBER 17, 2024

Our ecosystem enables engineering teams to run applications and services at scale, utilizing a mix of open-source and proprietary solutions. In turn, our self-serve platforms allow teams to create and deploy, sometimes custom, workloads more efficiently. The standardized data model and processing promotes scalability and consistency.

Efficiency 202

Efficiency Cloud Analytics Infrastructure 202