The Netflix TechBlog

NOVEMBER 20, 2023

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Processing 219

Processing Big Data Efficiency Engineering 219

The Netflix TechBlog

SEPTEMBER 10, 2024

The folks on the Cloud Data Engineering (CDE) team, the ones building the paved path for internal data at Netflix, graciously helped us scale it up and make adjustments, but it ended up being an involved process as we kept growing. As Pushy’s portfolio grew, we experienced some pain points with Dynomite.

Latency 234

Latency Cache Tuning Efficiency 234

The Netflix TechBlog

MAY 26, 2020

Spark could look up and retrieve the data in the s3 files that the Mouthful represented. This intermediate step of persisting Mouthfuls allowed us to easily “eat” through S3 event SQS messages at great speed, converting them to far fewer Mouthful SQS Messages which would each be consumed by a single Spark app instance.

Network 154

Network Tuning AWS Traffic 154

All Things Distributed

OCTOBER 7, 2015

While BI solutions have existed for decades, customers have told us that it takes an enormous amount of time, engineering effort, and money to bridge this gap. These solutions lack interactive data exploration and visualization capabilities, limiting most business users to canned reports and pre-selected queries.

Cloud 112

Cloud Big Data AWS Analytics 112

Abhishek Tiwari

DECEMBER 27, 2017

Data solution vendors like SnapLogic and Informatica are already developing machine learning and artificial intelligence (AI) based smart data integration assistants. These assistants can recommend next-best-action or suggest datasets, transforms, and rules to a data engineer working on a data integration project.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Abhishek Tiwari

JULY 20, 2019

Depending on work you can choose a smaller team of similar expertise (for example a team with mostly frontend engineers) or a smaller team of diverse expertise (team with balanced frontend, backend, data engineers). Thirdly, let engineers themselves choose the delivery teams and organise them around the initiative.

Engineering 61

Engineering Retail Airlines Healthcare 61

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

Testsigma

NOVEMBER 28, 2019

Udacity Udacity provides nanodegree programs on all automation languages like C++, Machine Learning, Data engineer, Robotics and more. Alternatively, you could also take the help of some amazing services to multiply the speed of testing by evaluating easy to use test automation tools like Testsigma with zero upfront investments.

Website 53

Website Testing Programming Automotive 53

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 221

Metrics Architecture Infrastructure Innovation 221

All Things Distributed

NOVEMBER 15, 2016

They require teams of data engineers to spend months building complex data models and synthesizing the data before they can generate their first report. The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations.

Analytics 123

Analytics Availability Media Social Media 123

O'Reilly

NOVEMBER 26, 2024

Entirely new paradigms rise quickly: cloud computing, data engineering, machine learning engineering, mobile development, and large language models. It’s less risky to hire adjunct professors with industry experience to fill teaching roles that have a vocational focus: mobile development, data engineering, and cloud computing.

Education 110

Education Azure AWS Java 110