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APACHE AIRFLOW
A platform to programmatically author, schedule, and monitor workflows
Apache 2.0
ABOUT
Orchestrating complex multi-step data pipelines across disparate systems is difficult without a centralized scheduler. Airflow solves this by allowing teams to define workflows as Python DAGs with built-in scheduling, retry logic, monitoring, alerting, and integrations across cloud providers, databases, and services.
INSTALL
pip install apache-airflowINTEGRATION GUIDE
1. Orchestrating ETL and ELT data pipelines and batch processing workflows
2. Scheduling and monitoring machine learning model training pipelines
3. Automating cloud infrastructure provisioning and data transfer jobs
4. Running data quality checks, validation, and reporting workflows
TAGS
workflow-orchestrationdata-pipelineETLschedulingDAGautomationdata-engineeringpython