GCP Data Analytics Pipeline
This diagram shows a common Google Cloud streaming analytics path. An application publishes events to Pub/Sub, which buffers and distributes the stream. Dataflow reads that stream and performs transformations before loading the results into BigQuery. Looker queries the warehouse for reporting. The drawing makes the handoff between event ingestion, processing, storage, and analysis visible. It is a useful starting point for product analytics, operational metrics, or event reporting. Add raw storage, a dead-letter topic, or scheduled jobs if those are essential to the design. Keep the diagram current when equipment, cable paths, service ownership, or security boundaries change, so it remains useful for planning and operations.
Open it in the AI editor with a prompt pre-filled — keep what works, change what doesn't.
Scenario
Streaming analytics
Key decisions
- Event intake: Pub/Sub decouples producers from processing.
- Transformation: Dataflow processes the stream.
- Warehouse: BigQuery stores analytics-ready data.
When to reuse this
Use this to explain a simple event-to-dashboard path on Google Cloud.
Frequently asked questions
What does Pub/Sub do?
Where does Dataflow fit?
Why use BigQuery in the diagram?
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