Dagster

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Dagster is an open-source data orchestration platform designed to help data engineers and scientists build, test, and monitor data pipelines. It provides a flexible Python API for defining data workflows, allowing users to create modular, reusable components called "assets" that represent data artifacts or computational steps. Dagster emphasizes data lineage and observability, enabling users to track the relationships between different data assets and understand how changes propagate through the system.

The platform supports various execution environments, including local development, containerized deployments, and cloud-native setups. Dagster integrates seamlessly with popular data tools and frameworks like Pandas, Spark, and dbt, making it easier to incorporate existing data processes into a unified workflow.

One of Dagster's key features is its web-based UI, which provides a visual representation of data pipelines, real-time execution monitoring, and debugging capabilities. This interface helps data teams collaborate more effectively and troubleshoot issues quickly.

For aspiring data professionals, Dagster offers a powerful way to structure and manage complex data workflows while promoting best practices in data engineering, such as testing, documentation, and version control integration.