The Netflix TechBlog

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie 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. Kevin, what drew you to data engineering?

Data Engineering 189

Data Engineering Engineering Entertainment Big Data 189

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. Late transformation.

Big Data 40

Big Data Retail Storage Google 40

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.” Netflix’s diverse data landscape made it challenging to capture all the right data and conforming it to a common data model.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 137

Cloud Big Data AWS Analytics 137

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 152

Analytics Availability Media Social Media 152