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Answer: Develop Airflow directed acyclic graphs in Python and run them using Cloud Composer.
The correct approach is to develop Airflow directed acyclic graphs in Python and execute them with Cloud Composer. Cloud Composer does not support SQL for writing directed acyclic graphs, and Cloud Workflows is designed for API workflows, not for handling complex batch job workflows. For more details, refer to [Google Cloud Composer documentation](https://cloud.google.com/composer).
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A team of data analysts is looking to execute a series of jobs on large datasets with complex dependencies between them. They prefer using a managed service. What would be your recommendation?
A
Develop Airflow directed acyclic graphs in SQL and run them using Cloud Workflows.
B
Develop Airflow directed acyclic graphs in Python and run them using Cloud Composer.
C
Develop Airflow directed acyclic graphs in SQL and run them using Cloud Composer.
D
Develop Airflow directed acyclic graphs in Python and run them using Cloud Workflows.
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