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1. Streamlining Membership Data Engineering at Netflix with Psyberg

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions.

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Data Ingestion: The First Step Towards a Flawless Data Pipeline

Simform

Data ingestion is the foremost layer in a data engineering pipeline, acting as a vital pillar in the overall analytics architecture. Thus, it is essential to implement data ingestion just right. Here is everything you need to know to take the first step toward a flawless data pipeline.

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Spice up your Analytics: Amazon QuickSight Now Generally Available in N. Virginia, Oregon, and Ireland.

All Things Distributed

The reality is that many traditional BI solutions are built on top of legacy desktop and on-premises architectures that are decades old. They require teams of data engineers to spend months building complex data models and synthesizing the data before they can generate their first report. How you can get started.

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

The Netflix TechBlog

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. All these micro-services are currently operated in AWS cloud infrastructure.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. Users configure the workflow to read the data in a window (e.g. The window is set based on users’ domain knowledge so that users have a high confidence that the late arriving data will be included or will not matter (i.e.

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What is IT automation?

Dynatrace

As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles. Big data automation tools. How organizations benefit from automating IT practices.

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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn more about other Data Science and Engineering functions at Netflix?