Microsoft DP-700 Practice Test 12
Question 110
A scientist wants to reuse Python libraries and implement multi-stage feature extraction in Spark. Which item should own the code?
- Use Dataflow Gen2 and choose its supported warehouse destination.
- Develop the transformation in a Spark notebook attached to an appropriate environment.
- Create a data pipeline with parameterized activities and retry/condition logic.
- Build a Dataflow Gen2 with the necessary Power Query steps and configured destination.
Explanation
Correct Answer
B:Notebooks express code-heavy distributed transformations and can share governed libraries through environments. Compare resulting features with expected test cases.
Incorrect Answers
A:A dataflow supports connector-based Power Query shaping and destinations without authoring an orchestration graph.
C:Pipeline orchestration handles multi-item dependencies and execution control without embedding scheduling logic in each notebook.
D:Dataflow Gen2 is designed for low-code transformations with reusable refresh behavior and data destinations.
Question 111
A team only needs to transform a CSV, change columns, and load a warehouse table with a graphical editor. Which item should they consider first?
- Develop the transformation in a Spark notebook attached to an appropriate environment.
- Use a Fabric Spark notebook with PySpark transformations.
- Use a Fabric data pipeline with dependent activities.
- Use Dataflow Gen2 and choose its supported warehouse destination.
Explanation
Correct Answer
D:A dataflow supports connector-based Power Query shaping and destinations without authoring an orchestration graph. Check the destination schema and row count after refresh.
Incorrect Answers
A:Notebooks express code-heavy distributed transformations and can share governed libraries through environments.
B:A notebook supports programmatic distributed processing and custom Python logic beyond basic visual data shaping.
C:Pipelines coordinate data movement and conditional execution across activities, unlike a transformation query by itself.
Question 112
A finance pipeline must run at 02:00 every weekday. Which trigger type matches this requirement?
- Configure a scheduled pipeline run with the required timezone and recurrence.
- Use null-safe access to trigger-event fields when testing outside the event context.
- Save the latest pipeline changes before the on-demand run.
- Define pipeline parameters and supply matching parameter names and values in each schedule.
Explanation
Correct Answer
A:A schedule supports time-based execution; file-arrival triggers do not establish a fixed business clock. Inspect upcoming schedule instances in the correct timezone.
Incorrect Answers
B:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values.
C:Unsaved editor changes do not become the executed pipeline definition when an on-demand run starts.
D:A schedule can provide run-time parameter values, but names must match the pipeline definitions exactly.
Question 113
An ingestion pipeline should run when a file lands in a specified storage path rather than polling hourly. What trigger should be chosen?
- Configure the schedule end date as well as the start date and recurrence.
- Configure a supported storage-event-based pipeline trigger for the target path.
- Save the latest pipeline changes before the on-demand run.
- Define pipeline parameters and supply matching parameter names and values in each schedule.
Explanation
Correct Answer
B:Event triggers react to the relevant file event and avoid needless fixed-interval checks. Upload a test file and correlate its triggered run.
Incorrect Answers
A:Fabric pipeline schedules include bounded start/end settings; setting only the recurrence does not express a planned stop.
C:Unsaved editor changes do not become the executed pipeline definition when an on-demand run starts.
D:A schedule can provide run-time parameter values, but names must match the pipeline definitions exactly.
Question 114
An engineer has modified a pipeline and immediately presses Run but sees prior logic. What prerequisite should be verified?
- Save the latest pipeline changes before the on-demand run.
- Configure a supported storage-event-based pipeline trigger for the target path.
- Define pipeline parameters and supply matching parameter names and values in each schedule.
- Use null-safe access to trigger-event fields when testing outside the event context.
Explanation
Correct Answer
A:Unsaved editor changes do not become the executed pipeline definition when an on-demand run starts. Compare the saved definition with the execution version.
Incorrect Answers
B:Event triggers react to the relevant file event and avoid needless fixed-interval checks.
C:A schedule can provide run-time parameter values, but names must match the pipeline definitions exactly.
D:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values.
Question 115
A pipeline schedule should stop automatically after the fiscal-year close. Which setting must be provided?
- Use null-safe access to trigger-event fields when testing outside the event context.
- Configure the schedule end date as well as the start date and recurrence.
- Configure a supported storage-event-based pipeline trigger for the target path.
- Save the latest pipeline changes before the on-demand run.
Explanation
Correct Answer
B:Fabric pipeline schedules include bounded start/end settings; setting only the recurrence does not express a planned stop. Check the saved schedule window.
Incorrect Answers
A:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values.
C:Event triggers react to the relevant file event and avoid needless fixed-interval checks.
D:Unsaved editor changes do not become the executed pipeline definition when an on-demand run starts.
Question 116
A pipeline scheduled for two regions must pass a region code for each run. What setting connects the schedule to its logic?
- Define pipeline parameters and supply matching parameter names and values in each schedule.
- Configure the schedule end date as well as the start date and recurrence.
- Use null-safe access to trigger-event fields when testing outside the event context.
- Save the latest pipeline changes before the on-demand run.
Explanation
Correct Answer
A:A schedule can provide run-time parameter values, but names must match the pipeline definitions exactly. Inspect the effective parameters of both regional runs.
Incorrect Answers
B:Fabric pipeline schedules include bounded start/end settings; setting only the recurrence does not express a planned stop.
C:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values.
D:Unsaved editor changes do not become the executed pipeline definition when an on-demand run starts.
Question 117
A daily scheduled load sometimes needs an emergency one-time replay. What run mechanism supports that without changing the schedule?
- Configure a supported storage-event-based pipeline trigger for the target path.
- Use null-safe access to trigger-event fields when testing outside the event context.
- Configure the schedule end date as well as the start date and recurrence.
- Start an on-demand pipeline run with the appropriate parameters.
Explanation
Correct Answer
D:An on-demand run is separate from the persisted schedule; it permits a controlled extra execution without modifying recurrence. Check that the schedule remains unchanged afterward.
Incorrect Answers
A:Event triggers react to the relevant file event and avoid needless fixed-interval checks.
B:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values.
C:Fabric pipeline schedules include bounded start/end settings; setting only the recurrence does not express a planned stop.
Question 118
A pipeline is triggered by new files, and debugging a manual run yields a null file name. Which expression design helps?
- Use null-safe access to trigger-event fields when testing outside the event context.
- Define pipeline parameters and supply matching parameter names and values in each schedule.
- Start an on-demand pipeline run with the appropriate parameters.
- Configure a scheduled pipeline run with the required timezone and recurrence.
Explanation
Correct Answer
A:Manual runs do not necessarily populate event metadata; safe access prevents errors while retaining real event values. Compare manual and event-triggered parameter output.
Incorrect Answers
B:A schedule can provide run-time parameter values, but names must match the pipeline definitions exactly.
C:An on-demand run is separate from the persisted schedule; it permits a controlled extra execution without modifying recurrence.
D:A schedule supports time-based execution; file-arrival triggers do not establish a fixed business clock.
Question 119
One pipeline loads many countries but must select a different source folder each run. Which pattern avoids cloning the pipeline?
- Read the upstream activity output using the pipeline expression language after enforcing success dependency.
- Use an If Condition activity with an expression against the prior activity's result.
- Define a country parameter and use it in a dynamic dataset or path expression.
- Use explicit expression-language type conversion before the numeric comparison.
Explanation
Correct Answer
C:Runtime parameters separate variable input paths from reusable activity logic. Run two country values and confirm distinct folders.
Incorrect Answers
A:Activity outputs can parameterize downstream operations when their completion and output schema are handled explicitly.
B:Conditional branching expresses execution logic based on data or metadata instead of running both branches unconditionally.
D:String comparisons can produce incorrect threshold decisions when numeric values have not been converted.
Question 120
A notebook activity must receive the pipeline's run date. How should the value cross the activity boundary?
- Use explicit expression-language type conversion before the numeric comparison.
- Use a dynamic expression referencing supported pipeline run metadata.
- Use an If Condition activity with an expression against the prior activity's result.
- Map a pipeline parameter or expression into the notebook activity's base parameters.
Explanation
Correct Answer
D:Notebook arguments must be explicitly supplied by the orchestrator; a notebook cannot safely assume the pipeline's parameter is a global variable. Inspect notebook parameter values in execution logs.
Incorrect Answers
A:String comparisons can produce incorrect threshold decisions when numeric values have not been converted.
B:Run metadata is available to pipeline expressions and creates traceable, per-run destinations.
C:Conditional branching expresses execution logic based on data or metadata instead of running both branches unconditionally.
