Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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Updated
Aug 19, 2024 - Python
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Workflow Engine for Kubernetes
Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code
PipelineAI
Build data pipelines, the easy way 🛠️
Docker Apache Airflow
Curated list of resources about Apache Airflow
DataSphereStudio is a one stop data application development& management portal, covering scenarios including data exchange, desensitization/cleansing, analysis/mining, quality measurement, visualization, and task scheduling.
Elyra extends JupyterLab with an AI centric approach.
A series of DAGs/Workflows to help maintain the operation of Airflow
Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.
Dynamically generate Apache Airflow DAGs from YAML configuration files
A Data Engineering & Machine Learning Knowledge Hub
Example end to end data engineering project.
More than 2000+ Data engineer interview questions.
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Personal Data Engineering Projects
Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.
The User-Community Airflow Helm Chart is the standard way to deploy Apache Airflow on Kubernetes with Helm. Originally created in 2017, it has since helped thousands of companies create production-ready deployments of Airflow on Kubernetes.
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