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Saturday, 27 April 2019

Apache Airflow using Google Cloud Composer: Introduction » SAVE 58% OFF!


Requirements
  • Google Cloud Platform Account OR even Free Trial account - NO Install required
  • Good understanding on Python code and some exposure to bash shell scripting will help.
Description
Apache Airflow is an open-source  platform to programmatically author, schedule and monitor workflows.
Cloud Composer  is a fully managed workflow orchestration service that empowers you to author, schedule, and monitor pipelines that span across clouds and on-premises data centers. Built on the popular Apache Airflow open source project and operated using the Python programming language, Cloud Composer is free from lock-in and easy to use.
With Apache Airflow hosted on cloud ('Google' Cloud composer) and hence,this will assist learner to focus on Apache Airflow product functionality and thereby learn quickly, without any hassles of having Apache Airflow installed locally on a machine.
Cloud Composer pipelines are configured as directed acyclic graphs (DAGs) using Python, making it easy for users of any experience level to author and schedule a workflow. One-click deployment yields instant access to a rich library of connectors and multiple graphical representations of your workflow in action, increasing pipeline reliability by making troubleshooting easy.
This course is designed with beginner in mind, that is first time users of cloud composer / Apache airflow. The course is structured in such a way that it has presentation to discuss the concepts initially and then  provides with hands on demonstration to make the understanding better.
The python DAG programs used in demonstration source file (9 Python files) are available for download toward further practice by students.
Happy learning!!!
Who this course is for:
  • People interested in Data warehousing, Big data, Data engineering
  • People interested in Automated tools for task workflow scheduling
  • Student interested to know about Airflow
  • Professional to wish to explore as how Apache Airflow can be used in Task scheduling and building Data pipelines