The modern data platform relies on dbt, a staple of the industry, but also requires tools to manage and monitor its various components. Python plays a crucial role in this ecosystem, particularly when it comes to executing complex computations or interacting with external APIs. Dagster, an orchestrator tool, provides a powerful solution for managing these workflows by offering software-defined assets, which enable cross-technology lineage, declarative data pipelines, detailed historical metadata, and the ability to orchestrate arbitrary Python within dbt projects. By leveraging these features, engineers can define and schedule jobs that update parts of their global graph, view the lineage of data as it moves between tools, and monitor the current state of all data assets in their platform. This approach simplifies the process of managing complex data workflows and provides a more efficient and scalable solution for companies looking to transform their data platforms.