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Exam Code: DP-700

Exam Name Implementing Data Engineering Solutions Using Microsoft Fabric

Certification Provider: Microsoft

Corresponding Certification: Microsoft Certified: Fabric Data Engineer Associate

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Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Practice Tests

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Microsoft DP-700 Practice Test 2

Question 10

A finance team rotates employees frequently and does not want to maintain hundreds of direct OneLake role members. Which engineering decision is most suitable for this specific situation?

  1. Assign the release lead the Member workspace role.
  2. Review supported audit events for role and permission changes.
  3. Assign a managed Microsoft Entra group to the OneLake security role.
  4. Check external collaboration and guest-access configuration in Microsoft Entra.

Explanation

Correct Answer

C:

OneLake security resolves supported Entra group membership for role grants.

Incorrect Answers

A:

Member includes item management and sharing without full Admin workspace deletion privileges.

B:

Audit logs provide available governance activity history for investigation.

D:

Guest identity settings can prevent OneLake role grants from being applied as expected.

Question 11

KQL telemetry stores utilization percentages as strings but average is required. What should the engineer implement first to satisfy the stated need?

  1. Convert values to numeric before KQL avg aggregation.
  2. Set an explicit decimal or numeric type in Power Query.
  3. Use T-SQL grouped aggregation on derived date and channel.
  4. Explicitly cast and parse the fields in PySpark.

Explanation

Correct Answer

A:

Numerical aggregation requires numeric typed input.

Incorrect Answers

B:

Explicit typing avoids text arithmetic and unstable inference.

C:

The composite group defines the target output grain.

D:

Typed transforms avoid storing measures as text.

Question 12

A Spark Structured Streaming job must survive notebook process failure without rereading the entire source indefinitely. Which action best addresses the requirement?

  1. Configure multiple appropriate destinations on the Eventstream.
  2. Use a stateful streaming join with a valid event-time bound and watermark policy.
  3. Configure a durable checkpoint location for the streaming query.
  4. Use deduplication keyed on event ID within a defined streaming state policy.

Explanation

Correct Answer

C:

Checkpoint metadata records stream processing progress for restart.

Incorrect Answers

A:

An Eventstream can route data from a source to more than one destination.

B:

Bounded joins limit held state and match related events by key and time.

D:

Keyed streaming deduplication limits duplicate business contributions.

Question 13

A pipeline runs daily but needs an alert email when a scheduled run fails and not when a manual run fails. Which engineering decision is most suitable for this specific situation?

  1. Create two schedules on the pipeline with their respective parameter values.
  2. Configure failure notifications on the scheduled pipeline run.
  3. Define pipeline parameters and reference them with dynamic content expressions.
  4. Configure success and failure activity dependencies for the downstream branches.

Explanation

Correct Answer

B:

Scheduled pipelines support configured failure notifications distinct from manual invocation.

Incorrect Answers

A:

Multiple schedules can invoke the same pipeline with different times and supplied parameters.

C:

Parameters make the same pipeline definition reusable with different runtime values.

D:

Activity dependency conditions explicitly control which path runs after an outcome.

Question 14

A long-running orchestration has repeated partial failures but operators need to identify the exact failed activity for targeted repair. Which action best addresses the requirement?

  1. Invoke the reusable pipeline through an Execute Pipeline activity.
  2. Inspect the pipeline's individual activity runs and their error outputs.
  3. Create two schedules on the pipeline with their respective parameter values.
  4. Reference the current loop item through the pipeline expression builder.

Explanation

Correct Answer

B:

Activity-level results expose the step and message causing an orchestration failure.

Incorrect Answers

A:

Child pipelines allow shared orchestration logic without cloning all activities.

C:

Multiple schedules can invoke the same pipeline with different times and supplied parameters.

D:

ForEach item expressions bind an activity's dynamic value to the current iteration.

Question 15

In a Microsoft Fabric solution, a large Spark fact joins a tiny lookup dimension that fits executor memory. Which configuration or implementation should the engineer choose?

  1. Normalize compatible join-key data types.
  2. Push selective filters before the expensive join.
  3. Use a suitable broadcast join.
  4. Use a skew-aware join plan or carefully designed salting.

Explanation

Correct Answer

C:

Broadcasting small lookup data can avoid shuffling the large fact.

Incorrect Answers

A:

Conversions on join paths can increase query cost.

B:

Earlier predicates reduce processed rows.

D:

Redistribution prevents one worker from becoming a straggler.

Question 16

Fabric capacity consumption spikes while pipelines and Spark jobs run concurrently. Which engineering decision is most suitable for this specific situation?

  1. Review the Fabric capacity metrics for the relevant capacity and time window.
  2. Check Eventhouse ingestion freshness and the dashboard query time range separately.
  3. Add data-quality reconciliation metrics to the monitoring gate.
  4. Inspect Copy activity input/output metrics and reconcile source and sink counts.

Explanation

Correct Answer

A:

Capacity metrics expose workload consumption, throttling, and pressure signals.

Incorrect Answers

B:

A stale visualization may result from query filtering rather than ingestion failure.

C:

Transport success does not prove that transformed business totals are correct.

D:

Copy statistics reveal transfer counts and possible skipped or rejected rows.

Question 17

An orchestration pipeline leaves downstream work pending because a success-only dependency follows an intentionally failed validation activity. What should the engineer implement first to satisfy the stated need?

  1. Define and provide the required pipeline parameter or safe default.
  2. Inspect evaluated dynamic expressions and correct the runtime source path.
  3. Correct the Copy mapping and type conversions for the affected columns.
  4. Correct the dependency branch conditions for the required outcome.

Explanation

Correct Answer

D:

A failure will not satisfy a success-only dependency in a pipeline graph.

Incorrect Answers

A:

Runtime parameters must exist with the names referenced by dynamic expressions.

B:

A wrong path can fail even when the connection itself is valid.

C:

Data type mismatch occurs at mapping or insert even when connectivity succeeds.

Question 18

A Dataflow Gen2 scheduled refresh did not update its destination table. Which action best addresses the requirement?

  1. Inspect the dataflow refresh history and detailed step errors.
  2. Check its refresh history and reported completion or error details.
  3. Inspect Copy activity input/output metrics and reconcile source and sink counts.
  4. Inspect Eventhouse ingestion and database monitoring metrics.

Explanation

Correct Answer

A:

Refresh history identifies dataflow execution status and transformation failures.

Incorrect Answers

B:

Semantic model refresh monitoring distinguishes successful updates from attempted refreshes.

C:

Copy statistics reveal transfer counts and possible skipped or rejected rows.

D:

Ingestion monitoring distinguishes source outages from slow arrival or indexing.

Question 19

Streaming source messages can arrive out of order, and a five-minute event-time aggregation must tolerate a bounded lateness window. What should the engineer implement first to satisfy the stated need?

  1. Backfill only the missing business-date partition with idempotent processing.
  2. Use event-time processing with a configured lateness or watermark policy.
  3. Deduplicate by stable event identifier within a defined retention or processing policy.
  4. Normalize event timestamps to a consistent time basis such as UTC.

Explanation

Correct Answer

B:

Event-time watermarks allow controlled late-arriving contributions before state is finalized.

Incorrect Answers

A:

A targeted backfill repairs the gap without unnecessarily reloading unrelated dates.

C:

Event-ID deduplication prevents redelivery from inflating event counts.

D:

A common time basis enables correct ordering and event-time grouping.

Question 20

A source-control commit for a lakehouse is expected to include the Files folder's customer CSVs, but only metadata appears in Git. Which action best addresses the requirement?

  1. Inspect and correct dependency mapping independently of the newly created lakehouse.
  2. Deploy lakehouse metadata while treating table data as separately managed.
  3. Keep lakehouse data files in governed storage and version only supported lakehouse metadata in Git.
  4. Commit the environment configuration and notebook changes together when both are supported.

Explanation

Correct Answer

C:

Git integration does not version the table data or Files contents of a lakehouse.

Incorrect Answers

A:

Default deployment behavior may provision an empty lakehouse even when references are mapped elsewhere.

B:

Lakehouse deployment and Git operations track metadata and definitions, not lakehouse table contents.

D:

Co-versioning dependencies avoids deploying code without required runtime configuration.