DZone

JANUARY 9, 2024

In the data-driven landscape of today, automation has become indispensable across industries, not just to maximize efficiency but, more importantly, to ensure quality. This holds true for the critical field of data engineering as well.

Data Engineering 140

Data Engineering Efficiency Engineering Testing 140

The Netflix TechBlog

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. What drew you to Netflix?

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

The Netflix TechBlog

MARCH 5, 2019

As a micro-service owner, a Netflix engineer is responsible for its innovation as well as its operation, which includes making sure the service is reliable, secure, efficient and performant. In the Efficiency space, our data teams focus on transparency and optimization.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

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. Partner oriented session getting everyone up to speed on what AWS sees as the customer needs, motivations, business outcomes and architectures around sustainability.

AWS 64

AWS Energy Architecture Programming 64

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 210

Processing Big Data Efficiency Engineering 210

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

SEPTEMBER 10, 2019

This enables us to optimize their experience at speed. Our data scientists faced numerous challenges in our previous infrastructure. Complex business logic was embedded directly into the ETL pipelines by data engineers. In order to replicate results, scientists had to delve deep into the data, code, and documentation.

Metrics 215

Metrics Architecture Infrastructure Innovation 215