Big Data Data Engineering Event 
The Netflix TechBlog
JUNE 20, 2024
A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.
The Netflix TechBlog
OCTOBER 28, 2021
Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Dynatrace
JULY 6, 2022
At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. When monitoring tools release a stream of alerts, teams can easily identify which ones are false and assess whether an event requires human intervention.
The Netflix TechBlog
MARCH 25, 2019
We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Data Enrichment The lineage data, when enriched with entity metadata and associated relationships, become more valuable to deliver on a rich set of business cases.
Abhishek Tiwari
DECEMBER 27, 2017
Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.
The Netflix TechBlog
DECEMBER 21, 2020
Some of the optimizations are prerequisites for a high-performance data warehouse. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster. Both automatic (event-driven) as well as manual (ad-hoc) optimization.
The Netflix TechBlog
MAY 26, 2020
It is easier to tune a large Spark job for a consistent volume of data. As you may know, S3 can emit messages when events (such as a file creation events) occur which can be directed into an AWS SQS queue. These events represent a specific cut of data from the table.
Expert insights. Personalized for you.
206 
Let's personalize your content