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Serverless Data Processing with Dataflow: Foundations

This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow. Prerequisites: The Serverless Data Processing with Dataflow course series builds on the concepts covered in the Data Engineering specialization. We recommend the following prerequisite courses: (i)Building batch data pipelines on Google Cloud : covers core Dataflow principles (ii)Building Resilient Streaming Analytics Systems on Google Cloud : covers streaming basics concepts like windowing, triggers, and watermarks >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

Status: Data Processing
Status: Google Cloud Platform
IntermediateCourse3 hours

Featured reviews

ZP

Reviewed Jul 29, 2024

Very useful to know. I found this course very interesting.

SR

Reviewed Apr 12, 2021

It would be better having detailed explanation of concepts for very beginners. This is a great course. Having detailed information will help learners learn quickly

RR

Reviewed Jun 12, 2022

L​ab is relatively scarce in relation to many concepts introduced in this course. More labs should be designed to help learners internalise the knowledge.

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