The DAG: Why Dependencies Form

Concepts covered: paDagOrchestration, paTopologicalOrder

A pipeline with one transform is a line: source, transform, destination. A pipeline with several transforms that depend on each other is a graph. The data engineering term for the structure is a directed acyclic graph, abbreviated DAG. Directed because data flows one way. Acyclic because no transform may depend, directly or indirectly, on its own output. Every modern orchestration tool, from Airflow to Dagster to Prefect, models pipelines as DAGs because the structure has the right properties: it is computable, it is debuggable, and it is impossible to deadlock. Anatomy of a DAG Why Cycles Are Forbidden A cycle in a dependency graph is a deadlock waiting to happen. If A depends on B, B depends on C, and C depends on A, the orchestrator cannot start any of them. Each is waiting for the othe

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This section is part of the What a Data Pipeline Is: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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