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Our First Netflix Data Engineering Summit

The Netflix TechBlog

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

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Overcoming Challenges and Best Practices for Data Migration From On-Premise to Cloud

DZone

Data migration is the process of moving data from one location to another, which is an essential aspect of cloud migration. Data migration involves transferring data from on-premise storage to the cloud. With the rapid adoption of cloud computing , businesses are moving their IT infrastructure to the cloud.

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Automated Testing in Data Engineering: An Imperative for Quality and Efficiency

DZone

This holds true for the critical field of data engineering as well. As organizations gather and process astronomical volumes of data, manual testing is no longer feasible or reliable. This comprehensive guide takes an in-depth look at automated testing in the data engineering domain.

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Offline Data Pipeline Best Practices Part 1:Optimizing Airflow Job Parameters for Apache Hive

DZone

Welcome to the first post in our exciting series on mastering offline data pipeline's best practices, focusing on the potent combination of Apache Airflow and data processing engines like Hive and Spark. Working together, they form the backbone of many modern data engineering solutions.

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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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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

This operational component places some cognitive load on our engineers, requiring them to develop deep understanding of telemetry and alerting systems, capacity provisioning process, security and reliability best practices, and a vast amount of informal knowledge about the cloud infrastructure.

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Friends don't let friends build data pipelines

Abhishek Tiwari

In recent times, in order to gain valuable insights or to develop the data-driven products companies such as Netflix, Spotify, Uber, AirBnB have built internal data pipelines. If built correctly, data pipelines can offer strategic advantages to the business. Depending on frameworks, data processing units (a.k.a

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