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A scheduled midnight ETL job overlaps its previous run when source processing takes more than twenty-four hours.
Which acceptance result most directly demonstrates that the intended solution works?
Uncontrolled overlap can cause competing writes and duplicated processing against the same target.
The notebook task completes on schedule with no interactive user logged into the workspace. That finding does not establish that a delayed run does not produce concurrent conflicting writes to the protected table.
The dashboard task begins after the source-refresh task succeeds and displays current facts. That finding does not establish that a delayed run does not produce concurrent conflicting writes to the protected table.
Runs start at the specified local weekday time and do not depend on a new source file. That finding does not establish that a delayed run does not produce concurrent conflicting writes to the protected table.
Operations wants a production notebook to execute as a scheduled workload even when the notebook author has logged out.
Which implementation decision best addresses this requirement?
Jobs launch reusable tasks independently of a developer's interactive notebook session. The selected implementation is the one directly aligned with the constraints in the scenario.
SQL tasks run governed queries as part of a DAG without requiring every step to be wrapped in a notebook.
Pipeline tasks are first-class job steps that can be sequenced with other supported task types.
An arrival trigger is data-driven and can avoid idle schedule executions when no files land.
Operations wants a production notebook to execute as a scheduled workload even when the notebook author has logged out.
Which acceptance result most directly demonstrates that the intended solution works?
Jobs launch reusable tasks independently of a developer's interactive notebook session.
The SQL task finishes under the service identity and the reporting table reflects the new aggregate. That finding does not establish that the notebook task completes on schedule with no interactive user logged into the workspace.
The validation notebook begins only after the pipeline reaches the intended successful state. That finding does not establish that the notebook task completes on schedule with no interactive user logged into the workspace.
Placing a qualifying new file in the watched location starts an eligible ingestion run. That finding does not establish that the notebook task completes on schedule with no interactive user logged into the workspace.
An analytics team needs a daily SQL query task that inserts aggregated results into a reporting table.
Which implementation decision best addresses this requirement?
SQL tasks run governed queries as part of a DAG without requiring every step to be wrapped in a notebook. The selected implementation is the one directly aligned with the constraints in the scenario.
DAG orchestration can coordinate analytics asset updates with data readiness.
Naming conventions do not replace formal DAG dependency definitions.
A table-update trigger aligns downstream processing with data changes rather than clock intervals.
An analytics team needs a daily SQL query task that inserts aggregated results into a reporting table.
Which acceptance result most directly demonstrates that the intended solution works?
SQL tasks run governed queries as part of a DAG without requiring every step to be wrapped in a notebook.
The dashboard task begins after the source-refresh task succeeds and displays current facts. That finding does not establish that the SQL task finishes under the service identity and the reporting table reflects the new aggregate.
The task graph displays the required execution sequence regardless of notebook filenames. That finding does not establish that the SQL task finishes under the service identity and the reporting table reflects the new aggregate.
A committed source update initiates the job while periods with no updates do not trigger redundant runs. That finding does not establish that the SQL task finishes under the service identity and the reporting table reflects the new aggregate.
A BI department wants its dashboard refresh orchestrated after new sales facts have landed.
Which implementation decision best addresses this requirement?
DAG orchestration can coordinate analytics asset updates with data readiness. The selected implementation is the one directly aligned with the constraints in the scenario.
Pipeline tasks are first-class job steps that can be sequenced with other supported task types.
Time-based triggers are appropriate when execution timing is mandated independently of event arrival.
A data-driven trigger can match work to actual upstream updates more efficiently than frequent polling.
A BI department wants its dashboard refresh orchestrated after new sales facts have landed.
Which acceptance result most directly demonstrates that the intended solution works?
DAG orchestration can coordinate analytics asset updates with data readiness.
The validation notebook begins only after the pipeline reaches the intended successful state. That finding does not establish that the dashboard task begins after the source-refresh task succeeds and displays current facts.
Runs start at the specified local weekday time and do not depend on a new source file. That finding does not establish that the dashboard task begins after the source-refresh task succeeds and displays current facts.
The new job runs when source data changes and does not run each idle minute. That finding does not establish that the dashboard task begins after the source-refresh task succeeds and displays current facts.
A platform team has a managed data pipeline asset that must run before a validation notebook.
Which implementation decision best addresses this requirement?
Pipeline tasks are first-class job steps that can be sequenced with other supported task types. The selected implementation is the one directly aligned with the constraints in the scenario.
Naming conventions do not replace formal DAG dependency definitions.
An arrival trigger is data-driven and can avoid idle schedule executions when no files land.
The business requirement is time-based, so file-dependent triggers could miss required clock boundaries.
A platform team has a managed data pipeline asset that must run before a validation notebook.
Which acceptance result most directly demonstrates that the intended solution works?
Pipeline tasks are first-class job steps that can be sequenced with other supported task types.
The task graph displays the required execution sequence regardless of notebook filenames. That finding does not establish that the validation notebook begins only after the pipeline reaches the intended successful state.
Placing a qualifying new file in the watched location starts an eligible ingestion run. That finding does not establish that the validation notebook begins only after the pipeline reaches the intended successful state.
Execution occurs at each required hour regardless of whether a file event was observed. That finding does not establish that the validation notebook begins only after the pipeline reaches the intended successful state.
An analyst has created five notebooks with numerical names and assumes Lakeflow Jobs will infer execution dependencies from their filenames.
Which implementation decision best addresses this requirement?
Naming conventions do not replace formal DAG dependency definitions. The selected implementation is the one directly aligned with the constraints in the scenario.
Time-based triggers are appropriate when execution timing is mandated independently of event arrival.
A table-update trigger aligns downstream processing with data changes rather than clock intervals.
A reliable clock schedule plus late-data logic satisfies a calendar reporting obligation better than assuming prompt file arrival.
An analyst has created five notebooks with numerical names and assumes Lakeflow Jobs will infer execution dependencies from their filenames.
Which acceptance result most directly demonstrates that the intended solution works?
Naming conventions do not replace formal DAG dependency definitions.
Runs start at the specified local weekday time and do not depend on a new source file. That finding does not establish that the task graph displays the required execution sequence regardless of notebook filenames.
A committed source update initiates the job while periods with no updates do not trigger redundant runs. That finding does not establish that the task graph displays the required execution sequence regardless of notebook filenames.
There is one scheduled daily run, and late arrivals are reconciled according to the documented policy. That finding does not establish that the task graph displays the required execution sequence regardless of notebook filenames.
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