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Explanation:

The best option for efficiently importing the proprietary flight data into BigQuery with minimal resource consumption is Option D – Use a custom connector with Apache Beam to write a Dataflow pipeline that streams the data into BigQuery in Avro format.

This approach is recommended because:

Apache Beam provides a flexible and powerful framework for building data pipelines.
The Avro format is optimized for streaming data, which helps in minimizing resource consumption.

Other options considered:

Option A involves using Apache Hive with Dataproc, which might not be as efficient for real-time streaming.
Option B suggests using batch jobs triggered by a shell script, which could be less efficient and more resource-intensive for real-time data.
Option C involves storing raw data first and transforming it later, which may require more resources and is less efficient for real-time streaming.

Explanation:

This approach is recommended because:

Apache Beam provides a flexible and powerful framework for building data pipelines.
The Avro format is optimized for streaming data, which helps in minimizing resource consumption.

Other options considered:

Option A involves using Apache Hive with Dataproc, which might not be as efficient for real-time streaming.
Option B suggests using batch jobs triggered by a shell script, which could be less efficient and more resource-intensive for real-time data.
Option C involves storing raw data first and transforming it later, which may require more resources and is less efficient for real-time streaming.

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A company in the aerospace industry has flight data stored in a proprietary format. You are tasked with importing this data into BigQuery efficiently, with minimal resource consumption. Which of the following options would you choose?

Real Exam

Last updated: February 25, 2026 at 14:03

Write a Dataproc job using Apache Hive to stream the data into BigQuery in CSV format.

3.7%

Use a shell script that triggers a Cloud Function for periodic ETL batch jobs on the new data source.

7.4%

Use a standard Dataflow pipeline to store the raw data in BigQuery, then transform the format later when the data is used.

33.3%

Use a custom connector with Apache Beam to write a Dataflow pipeline that streams the data into BigQuery in Avro format.

55.6%