Describe a real-world use case for using Step Functions with Lambda in a data workflow.

Use case: ML inference and reporting pipeline. Raw events land in S3; Lambda validates; Step Functions orchestrates: preprocessing Lambda → external ML API (wait) → result Lambda writes to DynamoDB/S3 → Slack summary. Why Step Functions + Lambda: Lambda = stateless, short compute; Step Functions = state, retries, branching, observability. Architectural trade-off: Express Workflows for high-volume, short runs (cheaper); Standard for long-running, complex branching. Cost: Step Functions charges per state transition; Lambda per invoke. For 10K events/day with Map state: ~100K transitions—cost is low. Pro-move: Parallel Map with Catch blocks for failure routing to DLQ; always define retry/backoff.