Concepts for Data Engineers: Task Management Tools
Data Orchestration is one of the hottest topics. Discover some of the most used tools.
As a data engineer, you understand the importance of efficient workflow management for successful data processing and transformation. Workflow management tools provide a systematic approach to orchestrating complex data pipelines, ensuring data integrity, and automating tasks. In this article, we will explore 4 popular workflow management tools: Apache Airflow, Azure Data Factory, Prefect, and Dagster. I will briefly discuss their benefits, use cases, and provide links to their official documentation for further exploration. Just a reminder, the tools in the market are not limited to it.
Apache Airflow:
Apache Airflow is an open-source platform that offers a flexible and extensible solution for workflow management. It allows you to define, schedule, and monitor workflows using Python code. Key benefits of Apache Airflow include:
