Dynatrace

JULY 6, 2022

And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues? Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. This requires significant data engineering efforts, as well as work to build machine-learning models.

Artificial Intelligence 191

Artificial Intelligence Tuning Strategy Big Data 191

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203

Storage Latency Efficiency Data Engineering 203

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Latency 63

Latency Analytics Scalability Engineering 63

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