Airflow
Map every DAG and task to the data assets it touches and the dashboards, metrics, and consumers that depend on the output.
Transformation & OrchestrationWhy Airflow matters
Airflow DAGs describe execution order, not data lineage. A DAG tells you task B runs after task A, but not which tables, columns, or metrics are affected. When a DAG fails or runs late, the on-call engineer knows something broke but has no visibility into which dashboards, reports, or business processes are impacted.
Typedef bridges the gap between Airflow execution graphs and actual data dependencies, giving you one connected view from DAG task through warehouse, transformation layer, and every downstream consumer.
What Typedef unlocks
Root cause tracing across the stack
When a DAG fails, trace the issue to its actual origin: a schema change in a source system, a stale ingestion job, or a modified transformation.
Blast radius for pipeline failures
Instantly see which dashboards, metrics, and business consumers are affected by a failed or delayed DAG, so triage is by impact, not guesswork.
Orchestration-to-lineage bridge
Connect Airflow task execution to the actual data dependencies it touches, from DAG through warehouse to every consumer.
DAG cleanup and migration
Safely refactor, consolidate, or retire DAGs with full visibility into every data asset and consumer that depends on them.
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