You're reading from Data Engineering with Google Cloud Platform - Second Edition

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Published inApr 2024

PublisherPackt

ISBN-139781835080115

Edition2nd Edition

Concepts

Data Engineering

Author (1)

Adi Wijaya

Understanding the working of Airflow

Airflow handles all three of the preceding elements using Python scripts. As data engineers, what we need to do is to create code in Python for handling task dependencies, scheduling our jobs, and integrating with other systems. This is different from traditional extract, transform, load (ETL) tools. If you have ever heard of or used tools such as Control-M, Informatica, Talend, or many other ETL tools, Airflow has the same positioning as these tools. The difference is that Airflow is not a user interface (UI)-based drag and drop tool. Airflow is designed for you to write the workflow using code.

There are a couple of good reasons why managing the workflow using code is a better idea than using drag-and-drop tools. Here’s why we should do this:

Using code, you can automate a lot of development and deployment processes
Using code, it’s easier for you to enable good testing practices
All the configurations can be managed...

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Data Engineering with Google Cloud Platform - Second Edition

Published in: Apr 2024Publisher: PacktISBN-13: 9781835080115

Author (1)

Adi Wijaya

Adi Widjaja is a strategic cloud data engineer at Google. He holds a bachelor's degree in computer science from Binus University and co-founded DataLabs in Indonesia. Currently, he dedicates himself to big data and analytics and has spent a good chunk of his career helping global companies in different industries.
Read more about Adi Wijaya

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You're reading from Data Engineering with Google Cloud Platform - Second Edition

Understanding the working of Airflow

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