需求
“Create a top-down cloud data lake architecture flowchart: operational databases, IoT, and logs enter batch or stream ingestion, then a raw data lake, processing, and a data-quality check. Send passing data to cleaned storage and a data catalog, failed data to quarantine, then serve analytics, machine-learning models, and data APIs to end users.”
接著試試Add a data-retention policy after the raw data lake.Add a data steward review for quarantined data.
這張圖裡有什麼
看懂背後的決策。
01
Ingestion method (batch vs. streaming) based on data velocity and latency requirements
02
Data quality check outcome (pass to clean zone, fail to quarantine)
Reusable for any cloud data lake implementation requiring scalable ingestion, storage, processing, and analytics, with configurable quality gates.