A data engineer configures a Databricks Lakeflow Job for daily customer data processing:Entry task: A...

Databricks Databricks-Certified-Data-Engineer-Associate Question Answer

A data engineer configures a Databricks Lakeflow Job for daily customer data processing:

Entry task: A single notebook loads raw data.

Parallel tasks:

A SQL query task performs data cleansing.

A notebook task performs feature engineering.

A pipeline task performs model updates.

Exit task: A dashboard refresh must run after all parallel tasks complete.

Requirement: Implement this dependency pattern using a DAG-based task graph.

Which task configuration ensures that all parallel tasks complete before the dashboard refresh task runs?

Configure the parallel tasks with sequential dependencies so that each task waits for the previous task to finish.

Add the dashboard task as dependent on all three parallel tasks using fan-in control flow.

Set the dashboard task to depend only on the SQL query task; the other tasks run independently.

Create separate Lakeflow Jobs for each parallel task and trigger them sequentially using external orchestration.

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