Dagster

Solution

A table (or file, or report) you declare with its dependencies; the scheduler materializes it. You are not scheduling a Python function that happens to write a table — you are scheduling the table.

Solution

dbt tests grain and relationships in the warehouse. Asset checks are the orchestrator saying this materialization is not fit for downstream. Both. Checks without dbt leave SQL untested. dbt without checks leave a green DAG on an empty table.

Solution

A full rebuild of every downstream asset. Partitioned assets + targeted backfill. If your graph cannot backfill one day, it is a batch script wearing assets.

Solution

A large heterogeneous ops estate, vendor sensors, and a team already staffed on Airflow. Move when the DAG is secretly a data graph and assets would delete half the glue. Fashion is not a reason.

Solution

In a resource / I/O manager, not in the op. Same rule as Airflow connections. If the PR has a password, it fails the screen.