Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 89 of 279

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

Google Professional Data Engineer Question 89

Select 3Google Cloud Platform

A retail company wants to create a data pipeline to process their real-time transactional data and store it in a data warehouse for analytics. The pipeline should include real-time ingestion, transformations, and the ability to query the data using SQL. Which combination of Google Cloud services would best accomplish this task?

  1. A

    Pub/Sub for real-time messaging and BigQuery for data warehousing

  2. B

    Dataflow for data transformations and BigQuery for data warehousing

  3. C

    Cloud Data Fusion for real-time ingestion and Hadoop for data warehousing

  4. D

    Dataproc for batch processing and Pub/Sub for real-time data ingestion

  5. E

    Pub/Sub for real-time messaging, Dataflow for transformations, and BigQuery for data warehousing

Show answer and explanation

Correct answers: A, B, E

Explanation

To build a real-time data pipeline for transactional data, you need services that handle ingestion, transformations, and storage for analytics. Pub/Sub is used for real-time messaging, Dataflow for processing and transformations, and BigQuery as the data warehouse for SQL-based queries. The combination of these services provides a robust, scalable, and efficient solution for the scenario.

  • A. Correct.

    Pub/Sub is ideal for ingesting real-time transactional data, and BigQuery serves as an effective data warehouse for analytics. However, this option does not address data transformation needs, which are crucial in this pipeline.

  • B. Correct.

    Dataflow is excellent for transformation tasks, and BigQuery is suitable for data warehousing. However, this option does not specify a real-time ingestion service like Pub/Sub.

  • C. Incorrect.

    Cloud Data Fusion is more geared towards batch data integration and does not provide real-time ingestion capabilities. Hadoop is not a native Google Cloud service and is less optimized for a modern analytics workflow compared to BigQuery.

  • D. Incorrect.

    Dataproc is typically used for batch processing, not real-time processing. Pub/Sub is valid for real-time ingestion, but the combination does not include a data warehouse for analytics.

  • E. Correct.

    This combination is the most comprehensive. Pub/Sub handles real-time messaging, Dataflow enables transformations, and BigQuery serves as the data warehouse, addressing all requirements of the pipeline.

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