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Databricks Certified Data Engineer - Professional

Databricks Certified Data Engineer - Professional

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In the context of designing a multi-task Databricks job on Microsoft Azure, where each task must only commence upon the successful completion of its predecessor to ensure data integrity and workflow correctness, which of the following approaches best aligns with Azure best practices for managing task dependencies and execution order? Consider factors such as cost-efficiency, scalability, and compliance with Azure's recommended patterns. Choose the best option from the following:

Simulated



Explanation:

Option B is correct because it directly addresses the requirement for sequential task execution with dependencies, aligning with Azure's best practices for workflow management. This approach ensures that each task only starts after its predecessor has successfully completed, maintaining data integrity and workflow correctness. It also leverages Azure's native features for task dependency management, offering a balance between cost-efficiency, scalability, and compliance with recommended patterns. Options A, C, and D either fail to properly manage task dependencies, introduce unnecessary complexity and cost, or risk compromising the workflow's integrity, making them less suitable for the described scenario.

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