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Google Professional Data Engineer practice question 66 of 279

Professional Data Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Data Engineer Question 66

Select 2Google Cloud Platform

You are designing a data pipeline to process incoming streaming data from IoT devices. The data needs to be ingested in real-time, processed to calculate aggregates like average temperature per device, and stored for further analysis. The solution must handle high throughput and ensure minimal data loss. Which Google Cloud services should you use to design this pipeline?

  1. A

    Cloud Pub/Sub for ingestion, Dataflow for processing, and BigQuery for storage

  2. B

    Cloud Storage for ingestion, Dataproc for processing, and Bigtable for storage

  3. C

    Cloud Pub/Sub for ingestion, Dataproc for processing, and BigQuery for storage

  4. D

    Cloud Pub/Sub for ingestion, Dataflow for processing, and Cloud Storage for storage

  5. E

    Cloud SQL for ingestion, Dataflow for processing, and BigQuery for storage

Show answer and explanation

Correct answers: A, C

Explanation

To design a real-time streaming data pipeline, Cloud Pub/Sub is used for efficient, scalable ingestion of high-throughput data streams. Dataflow or Dataproc can be used for stream processing depending on the complexity and tools preferred. For storage, BigQuery is a highly scalable, analytical database optimized for querying aggregate data. Cloud Storage, Cloud SQL, and other tools do not fully satisfy the requirements of real-time ingestion, processing, and analytical storage.

  • A. Correct.

    Correct. Cloud Pub/Sub provides real-time ingestion for high-throughput data streams, Dataflow is suitable for stream processing, and BigQuery is optimal for analytical storage.

  • B. Incorrect.

    Incorrect. Cloud Storage is not designed for real-time ingestion, and Dataproc is better suited for batch processing rather than real-time stream processing.

  • C. Correct.

    Correct. Cloud Pub/Sub is ideal for real-time ingestion, Dataproc can handle stream processing using tools like Spark Streaming, and BigQuery is a great choice for storing processed aggregate data.

  • D. Incorrect.

    Incorrect. While Cloud Pub/Sub and Dataflow are correct for ingestion and processing, Cloud Storage is not ideal for storing analytical data used for querying.

  • E. Incorrect.

    Incorrect. Cloud SQL is not suitable for ingesting high-throughput streaming data, as it is a relational database designed for other use cases.

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