Big Data Data Engineering Efficiency Metrics 
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. Backfill: Backfilling datasets is a common operation in big data processing.
The Netflix TechBlog
MARCH 25, 2019
Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
The Netflix TechBlog
SEPTEMBER 10, 2019
ABlaze: The standard view of analyses in the XP UI Suppose you’re running a new video encoding test and theorize that the two new encodes should reduce play delay, a metric describing how long it takes for a video to play after you press the start button. Our data scientists faced numerous challenges in our previous infrastructure.
The Netflix TechBlog
SEPTEMBER 18, 2020
I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. Julie] Chris and I have the same primary stakeholders (or engineering team that we support): Encoding Technologies. It’s one big optimization problem that requires balancing several different factors.
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.
Expert insights. Personalized for you.
210 
Let's personalize your content