The DAG: Tasks, Edges, No Cycles

Concepts covered: paDagOrchestration, paTaskDependency

Every modern orchestrator models a pipeline as a directed acyclic graph, abbreviated DAG. The structure is a small mathematical object with three properties. It has nodes (the tasks). It has edges (the dependencies). The edges point in one direction, and they cannot form a loop. Those properties are not stylistic preferences. They are the conditions that make the graph computable: a structure with cycles cannot be scheduled at all, and a structure without direction cannot be ordered. Vocabulary, Once and Precisely Why Direction Matters A pipeline that runs tasks in any order produces undefined results. The clean step needs the raw rows; running the clean step before the extract finishes means cleaning yesterday's rows or no rows at all. The direction on each edge encodes the temporal order

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This section is part of the Orchestration and Dependencies: Beginner 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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