1.3. The Data Lifecycle Model

💡 First Principle: Data flows through predictable stages, and each stage has specialized services. Understanding this flow helps you identify which service handles which job. No single service does everything well—that's why we chain specialists together.

Think of it like a factory assembly line: raw materials enter (ingestion), get processed at stations (transformation), stored in warehouses (data lakes), and delivered as finished products (reports). Each station is optimized for one job.

⚠️ Exam Trap: a service showing up at more than one stage. Synapse both stores and processes; Fabric spans all four. The fact that a service can occupy a stage does not make it the answer — read the requirement for which stage it actually names, then choose the service built for that job.