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Informative Article | Engineering Science | India | Volume 9 Issue 10, October 2020 | Rating: 3.9 / 10
ETL Automation and Orchestration with Apache Airflow
Ravi Shankar Koppula
Abstract: In the contemporary landscape of data engineering, ETL (Extract, Transform, Load) processes are pivotal for efficient data management and analytics. Apache Airflow has emerged as a powerful platform for orchestrating complex ETL workflows, offering robust capabilities for automation, scheduling, and monitoring. This article delves into the core functionalities and architecture of Apache Airflow, illustrating its efficacy in managing ETL pipelines. It covers the creation and management of Directed Acyclic Graphs (DAGs), task scheduling, and execution, as well as integration with various external systems. Additionally, the article highlights best practices for optimizing performance and ensuring reliability in ETL operations. Through comprehensive examples and case studies, readers will gain insights into the practical application of Apache Airflow for streamlined data workflows, ultimately enhancing data processing efficiency and accuracy.
Keywords: ETL Automation, Data Orchestration, Apache Airflow, Directed Acyclic Graph (DAG), Task Scheduling, Workflow Management, Data Integration, Monitoring and Logging, Data Engineering, Performance Optimization
Edition: Volume 9 Issue 10, October 2020,
Pages: 1809 - 1814