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Data Engineers of Netflix?—?Interview with Kevin Wylie

The Netflix TechBlog

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?

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Data Engineers of Netflix?—?Interview with Dhevi Rajendran

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Dhevi Rajendran Dhevi Rajendran This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Data Engineers of Netflix?—?Interview

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Data Engineers of Netflix?—?Interview with Samuel Setegne

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. What drew you to Netflix?

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Choosing an OLAP Engine for Financial Risk Management: What To Consider?

DZone

From a data engineer's point of view, financial risk management is a series of data analysis activities on financial data. The financial sector imposes its unique requirements on data engineering. Before they adopted an OLAP engine, they were using Kettle to collect data.

FinTech 130
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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. Its major advantages are below: Integrated intelligence. Multi-objective optimizations.

Tuning 210
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Since then, open-source Metaflow has gained support for Argo Workflows , a Kubernetes-native orchestrator, as well as support for Airflow which is still widely used by data engineering teams. Although details have evolved a lot, this old talk still gives a good overview of the service.

Systems 226
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What is IT automation?

Dynatrace

As digital services become more complex and numerous, organizations need IT automation to address the challenges of maintaining those services. With ever-evolving infrastructure, services, and business objectives, IT teams can’t keep up with routine tasks that require human intervention. Big data automation tools.