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How to Implement a Data Pipeline Using Amazon Web Services?

Analytics Vidhya

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary. appeared first on Analytics Vidhya.

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Data Pipeline Observability: A Model For Data Engineers

Databand.ai

Data Pipeline Observability: A Model For Data Engineers Eitan Chazbani June 29, 2023 Data pipeline observability is your ability to monitor and understand the state of a data pipeline at any time. We believe the world’s data pipelines need better data observability.

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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog: Data Engineering

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. They transform data into a consistent format for users to consume.

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How to learn data engineering

Christophe Blefari

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

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Data Engineering Weekly #151

Data Engineering Weekly

Github writes an excellent blog to capture the current state of the LLM integration architecture. link] Microsoft: Generative AI for Beginners Understanding Gen-AI becomes a mandatory skill for application developers and data engineers. Netflix writes about its membership data pipeline and how it supports the lookback approach.

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Data Engineering Weekly #161

Data Engineering Weekly

Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup. There will be food, networking, and real-world talks around data engineering. The article concludes with a look at data contracts as a concrete example of these principles in practice.

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1. Streamlining Membership Data Engineering at Netflix with Psyberg

Netflix Tech

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.