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 130

Data Engineering Efficiency Engineering Testing 130

The Netflix TechBlog

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

Data Engineering 259

Data Engineering Engineering Software Engineering Best Practices 259

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 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.

Tuning 210

Tuning Efficiency Big Data Engineering 210

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. Testing automation can be painstaking. Read eBook now!

Artificial Intelligence 198

Artificial Intelligence Tuning Strategy Big Data 198

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. Introduction Netflix relies on data to power its business in all phases.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

JANUARY 11, 2022

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243