what is dagster

Dagster is a data orchestrator. It is designed to organize and manage the complexity of data workflows, such as those involving Spark code and various deployment setups. Dagster introduces a data-aware, typed, self-describing, logical orchestration graph that models the structure inherent in every data application and platform. This orchestration graph is a key part of the entire application lifecycle and can serve as the foundation for a range of tools and libraries. The platform targets two primary audiences: full-stack engineers and data scientists responsible for end-to-end data applications and infrastructure, as well as platform teams that enable other data teams to efficiently and autonomously deliver features and capabilities. Dagster is flexible and adaptable, designed to run any tool, use any storage, and deploy to any infrastructure. Dagster's unique focus on data pipelines encourages the creation of data assets, such as files, tables, or ML models, rather than just executing tasks. This approach provides clear data lineage, making dependencies transparent within individual pipelines and across the entire data platform. It also clarifies the relationship between tasks and data assets, aiding in maintainability and understanding of the data workflows. In summary, Dagster is a new type of workflow engine that acts as a data orchestrator, providing a structured and clear way to manage complex data systems and facilitate collaboration between different roles involved in data processing.

@Scout what did I just ask you

Apologies for any confusion. You asked, "what is dagster?" In response, I provided an overview of Dagster as a data orchestrator and its role in managing data workflows. If you have any more specific questions or need further clarification about Dagster, please feel free to ask!