GCP Data Analytics Pipeline Diagram

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.

類型 網路圖標準 Cisco-convention topology icons引擎 schematex-network更新時間 2026/9/24

需求

“A GCP data analytics pipeline: application events publish to Pub/Sub, Dataflow transforms the stream into BigQuery, and a Looker dashboard queries BigQuery.”

接著試試Add Cloud Storage for raw event archivesAdd a dead-letter topic beside Pub/Sub

這張圖裡有什麼

看懂背後的決策。

01Event intake

Pub/Sub decouples producers from processing.

02Transformation

Dataflow processes the stream.

03Warehouse

BigQuery stores analytics-ready data.

Use this to explain a simple event-to-dashboard path on Google Cloud.

瀏覽所有網路圖範本 →

常見問題

What does Pub/Sub do?

Pub/Sub receives and distributes messages between event producers and consumers.

Where does Dataflow fit?

Dataflow transforms or processes data between ingestion and its destination.

Why use BigQuery in the diagram?

BigQuery is the warehouse that the dashboard queries in this example.