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Data Engineering Pipeline Management with Apache Airflow

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Take a deeper dive into data engineering pipeline management using Apache Airflow. In this course, certified Google cloud architect and data engineer Janani Ravi guides you through using Apache Airflow to complete your data engineering pipeline management workflows. Learn how to work with role-based access control, including creating users with different roles, executing a branching DAG and a SQL DAG, recalling actions that users with different roles can perform, and more. Go over how to manage SLAs and schedule DAGs with datasets. Find out how to work with AirFlow plugins and explore the CSV reader plugin. Plus, discover how to scale Apache Airflow, set up a data transformation pipeline, execute tasks, and more.

This course was created by Janani Ravi. We are pleased to host this training in our library.


01 - Introduction
  • 01 - Features for data engineering pipeline management

  • 02 - 1. Working with Role-Based Access Control
  • 01 - Prerequisites
  • 02 - Quick install overview
  • 03 - Creating an admin user and exploring roles
  • 04 - Creating users with different roles
  • 05 - Executing a simple branching DAG
  • 06 - Executing a simple SQL DAG
  • 07 - The public and viewer roles
  • 08 - The user role
  • 09 - The op role
  • 10 - Actions, resources, and permissions
  • 11 - Adding permissions to the public role
  • 12 - Creating and configuring a custom role

  • 03 - 2. Managing SLAs
  • 01 - Configuring emails for SLA management
  • 02 - Configuring task-level SLAs
  • 03 - Triggering and viewing SLA misses
  • 04 - Configuring DAG-level SLAs
  • 05 - Configuring DAG failed action

  • 04 - 3. Scheduling DAGs with Datasets
  • 01 - Dataset producer pipeline
  • 02 - Dataset consumer pipeline
  • 03 - Data-aware scheduling
  • 04 - Purchases producer pipeline and join pipeline
  • 05 - Data-aware scheduling with multiple datasets

  • 05 - 4. Working with Airflow Plugins
  • 01 - Introducing plugins
  • 02 - Adding menu items using plugins
  • 03 - Exploring the CSV reader plugin
  • 04 - Implementing the CSV reader plugin

  • 06 - 5. Scaling Airflow
  • 01 - Scaling Apache Airflow
  • 02 - Basic setup for the transformation pipeline
  • 03 - DAG for the transformation pipeline
  • 04 - Install RabbitMQ on macOS and Linux
  • 05 - Set up an admin user for RabbitMQ
  • 06 - Configuring the CeleryExecutor for Airflow
  • 07 - Executing tasks on a single Celery worker
  • 08 - Executing tasks on multiple Celery workers
  • 09 - Assigning tasks to queues

  • 07 - Conclusion
  • 01 - Summary and next steps
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