You are building an ML model to detect anomalies in real-time sensor data. You will use Pub/Sub to handle incoming requests. You want to store the results for analytics and visualization. How should y

The correct answer is A. 1 = Dataflow, 2 = AI Platform, 3 = BigQuery. Dataflow for the pipeline, BigQuery for storing and visualization and Platform AI (now Vertex) to build the model. https://cloud.google.com/architecture/building-anomaly-detection-dataflow-bigqueryml-dlp

Submitted by fatema_kw· Apr 18, 2026ML pipeline operationalization

Question

You are building an ML model to detect anomalies in real-time sensor data. You will use Pub/Sub to handle incoming requests. You want to store the results for analytics and visualization. How should you configure the pipeline?

Options

A1 = Dataflow, 2 = AI Platform, 3 = BigQuery
B1 = DataProc, 2 = AutoML, 3 = Cloud Bigtable
C1 = BigQuery, 2 = AutoML, 3 = Cloud Functions
D1 = BigQuery, 2 = AI Platform, 3 = Cloud Storage

How the community answered

(40 responses)

A
70% (28)
B
8% (3)
C
18% (7)
D
5% (2)

Explanation

Dataflow for the pipeline, BigQuery for storing and visualization and Platform AI (now Vertex) to build the model. https://cloud.google.com/architecture/building-anomaly-detection-dataflow-bigqueryml-dlp

Topics

#Real-time ML pipelines#Streaming data processing#ML model serving#Data warehousing

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