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Microsoft DP-700 Bundle

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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Microsoft DP-700 Practice Test 66

Question 650

A OneLake shortcut stops working after a source data migration. The current environment exhibits the following problem: the target table is accessible but queries run slowly through standard external scans. Which action should the team take next?

  1. Update the shortcut target and validate the new path
  2. Refresh external table schema and query acceleration metadata as appropriate
  3. Rotate the approved connection credential and retest bucket scope
  4. Evaluate eligible query acceleration or materialization based on access patterns

Explanation

Correct Answer

D:

Evaluate eligible query acceleration or materialization based on access patterns. Remote scans are a performance issue distinct from link validity.

Incorrect Answers

A:

The source Delta target was moved to a new path. A shortcut is a pointer whose target must exist.

B:

External Delta schema changed and Eventhouse shortcuts produce wrong column errors. External query schema must match the referenced Delta layout.

C:

A delegated S3 shortcut returns source access denied after credential expiry. Delegated shortcuts use stored source authentication.

Question 651

A scheduled notebook activity fails while its interactive version succeeds. An acceptance test shows that the pipeline uses a service identity lacking access to the Lakehouse. What should the administrator implement or verify?

  1. Grant the required Lakehouse read/write privileges to the execution identity
  2. Compare runtime duration with pipeline activity timeout settings
  3. Align the supported runtime, libraries and environment binding
  4. Validate parameter mappings and types before notebook execution

Explanation

Correct Answer

A:

Grant the required Lakehouse read/write privileges to the execution identity. Scheduled and interactive contexts may have different rights.

Incorrect Answers

B:

The scheduled activity times out but interactive execution finishes eventually. Invocation timeout can end a healthy but slow notebook.

C:

A scheduled run uses a different Fabric environment from the interactive test. Environment drift can explain different code behavior.

D:

The pipeline passes a null parameter that the notebook treats as an integer. Type mismatches can fail transformations or select no data.

Question 652

A scheduled notebook activity fails while its interactive version succeeds. The engineer has established the following constraint: the pipeline passes a null parameter that the notebook treats as an integer. Which option directly handles this observed condition?

  1. Rebind the default target item to the production Lakehouse
  2. Validate parameter mappings and types before notebook execution
  3. Grant the required Lakehouse read/write privileges to the execution identity
  4. Align the supported runtime, libraries and environment binding

Explanation

Correct Answer

B:

Validate parameter mappings and types before notebook execution. Type mismatches can fail transformations or select no data.

Incorrect Answers

A:

A deployed notebook points at a Lakehouse from development. Item binding must match the destination workspace.

C:

The pipeline uses a service identity lacking access to the Lakehouse. Scheduled and interactive contexts may have different rights.

D:

A scheduled run uses a different Fabric environment from the interactive test. Environment drift can explain different code behavior.

Question 653

A scheduled notebook activity fails while its interactive version succeeds. During an operations handoff, engineers find that a deployed notebook points at a Lakehouse from development. What is the most defensible next action?

  1. Compare runtime duration with pipeline activity timeout settings
  2. Grant the required Lakehouse read/write privileges to the execution identity
  3. Align the supported runtime, libraries and environment binding
  4. Rebind the default target item to the production Lakehouse

Explanation

Correct Answer

D:

Rebind the default target item to the production Lakehouse. Item binding must match the destination workspace.

Incorrect Answers

A:

The scheduled activity times out but interactive execution finishes eventually. Invocation timeout can end a healthy but slow notebook.

B:

The pipeline uses a service identity lacking access to the Lakehouse. Scheduled and interactive contexts may have different rights.

C:

A scheduled run uses a different Fabric environment from the interactive test. Environment drift can explain different code behavior.

Question 654

A scheduled notebook activity fails while its interactive version succeeds. The team observes that a scheduled run uses a different Fabric environment from the interactive test. Which technical choice fits this evidence?

  1. Grant the required Lakehouse read/write privileges to the execution identity
  2. Validate parameter mappings and types before notebook execution
  3. Align the supported runtime, libraries and environment binding
  4. Compare runtime duration with pipeline activity timeout settings

Explanation

Correct Answer

C:

Align the supported runtime, libraries and environment binding. Environment drift can explain different code behavior.

Incorrect Answers

A:

The pipeline uses a service identity lacking access to the Lakehouse. Scheduled and interactive contexts may have different rights.

B:

The pipeline passes a null parameter that the notebook treats as an integer. Type mismatches can fail transformations or select no data.

D:

The scheduled activity times out but interactive execution finishes eventually. Invocation timeout can end a healthy but slow notebook.

Question 655

A scheduled notebook activity fails while its interactive version succeeds. The implementation review confirms that the scheduled activity times out but interactive execution finishes eventually. Which step preserves the intended data behavior?

  1. Validate parameter mappings and types before notebook execution
  2. Align the supported runtime, libraries and environment binding
  3. Rebind the default target item to the production Lakehouse
  4. Compare runtime duration with pipeline activity timeout settings

Explanation

Correct Answer

D:

Compare runtime duration with pipeline activity timeout settings. Invocation timeout can end a healthy but slow notebook.

Incorrect Answers

A:

The pipeline passes a null parameter that the notebook treats as an integer. Type mismatches can fail transformations or select no data.

B:

A scheduled run uses a different Fabric environment from the interactive test. Environment drift can explain different code behavior.

C:

A deployed notebook points at a Lakehouse from development. Item binding must match the destination workspace.

Question 656

A Fabric pipeline intermittently produces duplicated destination rows. A scheduled execution exposes this issue: a copy step retries after its destination accepted an unacknowledged batch. What should the administrator implement or verify?

  1. Prevent overlapping conflicting writes or isolate staging by run
  2. Add idempotent target merge or run deduplication keyed by source identity
  3. Deduplicate using stable event/file version identifiers
  4. Deduplicate to one deterministic source row per target key

Explanation

Correct Answer

B:

Add idempotent target merge or run deduplication keyed by source identity. Retried acknowledgments may replay already persisted changes.

Incorrect Answers

A:

Two scheduled runs overlap and write the same partition. Concurrent runs can duplicate or conflict on shared state.

C:

A file trigger fires twice for the same storage event. Deduplicate using stable event/file version identifiers is relevant where a file trigger fires twice for the same storage event.

D:

A downstream MERGE matches duplicate source keys and generates inconsistent updates. Stable merge behavior requires unique match candidates.

Question 657

A Fabric pipeline intermittently produces duplicated destination rows. Data validation establishes that two scheduled runs overlap and write the same partition. Which option directly handles this observed condition?

  1. Commit state only after the durable sink operation succeeds
  2. Deduplicate to one deterministic source row per target key
  3. Prevent overlapping conflicting writes or isolate staging by run
  4. Deduplicate using stable event/file version identifiers

Explanation

Correct Answer

C:

Prevent overlapping conflicting writes or isolate staging by run. Concurrent runs can duplicate or conflict on shared state.

Incorrect Answers

A:

A watermark is advanced before destination commit. Failed writes must not advance the incremental boundary.

B:

A downstream MERGE matches duplicate source keys and generates inconsistent updates. Stable merge behavior requires unique match candidates.

D:

A file trigger fires twice for the same storage event. Deduplicate using stable event/file version identifiers would address a different failure: a file trigger fires twice for the same storage event.

Question 658

A Fabric pipeline intermittently produces duplicated destination rows. The production incident report states that a file trigger fires twice for the same storage event. What is the most defensible next action?

  1. Commit state only after the durable sink operation succeeds
  2. Deduplicate using stable event/file version identifiers
  3. Prevent overlapping conflicting writes or isolate staging by run
  4. Add idempotent target merge or run deduplication keyed by source identity

Explanation

Correct Answer

B:

Deduplicate using stable event/file version identifiers. Event delivery can repeat.

Incorrect Answers

A:

A watermark is advanced before destination commit. Failed writes must not advance the incremental boundary.

C:

Two scheduled runs overlap and write the same partition. Concurrent runs can duplicate or conflict on shared state.

D:

A copy step retries after its destination accepted an unacknowledged batch. Retried acknowledgments may replay already persisted changes.

Question 659

A Fabric pipeline intermittently produces duplicated destination rows. A postdeployment check reveals that a watermark is advanced before destination commit. Which technical choice fits this evidence?

  1. Prevent overlapping conflicting writes or isolate staging by run
  2. Deduplicate using stable event/file version identifiers
  3. Commit state only after the durable sink operation succeeds
  4. Deduplicate to one deterministic source row per target key

Explanation

Correct Answer

C:

Commit state only after the durable sink operation succeeds. Failed writes must not advance the incremental boundary.

Incorrect Answers

A:

Two scheduled runs overlap and write the same partition. Concurrent runs can duplicate or conflict on shared state.

B:

A file trigger fires twice for the same storage event. Deduplicate using stable event/file version identifiers would address a different failure: a file trigger fires twice for the same storage event.

D:

A downstream MERGE matches duplicate source keys and generates inconsistent updates. Stable merge behavior requires unique match candidates.

Question 660

A Fabric pipeline intermittently produces duplicated destination rows. The current environment exhibits the following problem: a downstream MERGE matches duplicate source keys and generates inconsistent updates. Which step preserves the intended data behavior?

  1. Deduplicate using stable event/file version identifiers
  2. Prevent overlapping conflicting writes or isolate staging by run
  3. Deduplicate to one deterministic source row per target key
  4. Commit state only after the durable sink operation succeeds

Explanation

Correct Answer

C:

Deduplicate to one deterministic source row per target key. Stable merge behavior requires unique match candidates.

Incorrect Answers

A:

A file trigger fires twice for the same storage event. Deduplicate using stable event/file version identifiers would address a different failure: a file trigger fires twice for the same storage event.

B:

Two scheduled runs overlap and write the same partition. Concurrent runs can duplicate or conflict on shared state.

D:

A watermark is advanced before destination commit. Failed writes must not advance the incremental boundary.