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Answer: 1 = Dataflow, 2 = AI Platform, 3 = BigQuery
The correct answer is A: 1 = Dataflow, 2 = AI Platform, 3 = BigQuery. Dataflow is essential for handling real-time data processing and transformations. AI Platform is suitable for deploying and managing ML models to detect anomalies. BigQuery is used for storing processed data and allows for powerful analytics and visualization. This combination ensures an efficient and scalable pipeline to meet the requirements of real-time anomaly detection from sensor data.
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You are tasked with building a machine learning model to detect anomalies in real-time sensor data from IoT devices. You plan to use Google Cloud Pub/Sub to manage the incoming data streams. Once the anomalies are detected, you need to store the results so they can be used for further analytics and visualization. Considering these requirements, how should you configure your data processing and storage pipeline in Google Cloud?
A
1 = Dataflow, 2 = AI Platform, 3 = BigQuery
B
1 = DataProc, 2 = AutoML, 3 = Cloud Bigtable
C
1 = BigQuery, 2 = AutoML, 3 = Cloud Functions
D
1 = BigQuery, 2 = AI Platform, 3 = Cloud Storage