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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 70

Question 690

A Dataflow Gen2 job fails with a mix of privacy and credential errors. The current environment exhibits the following problem: source API returns too many pages and the dataflow times out. Which step preserves the intended data behavior?

  1. Evaluate pagination, folding and alternative scalable extraction patterns
  2. Configure legitimate supported privacy levels and connection scope
  3. Add null-safe logic while preserving intended missing-data semantics
  4. Reauthorize the dataflow connection with an approved principal

Explanation

Correct Answer

A:

Evaluate pagination, folding and alternative scalable extraction patterns. Performance and source response behavior can exceed refresh limits.

Incorrect Answers

B:

A cross-source Power Query merge violates configured data privacy boundaries. Dataflow source privacy handling controls permissible combination paths.

C:

A custom M expression fails only for null input values. A conversion must handle optional fields explicitly.

D:

A refresh fails because the identity lost source read rights. Data source permissions apply at refresh execution.

Question 691

A warehouse SQL engineer investigates failed joins and transformations. An acceptance test shows that an UPDATE targets the wrong schema because object names are unqualified. What is the best engineering response?

  1. Move predicates to the intended pre/postaggregation stage and test output
  2. Test the predicate under the actual execution principal and correct authorized grants
  3. Use explicit schema-qualified table references and validate context
  4. Identify invalid values with TRY_CONVERT and quarantine the offending records

Explanation

Correct Answer

C:

Use explicit schema-qualified table references and validate context. Schema qualification avoids accidental resolution.

Incorrect Answers

A:

A GROUP BY result differs from expected totals due to misplaced WHERE filters. WHERE and HAVING apply at different query-processing stages.

B:

A new row-level security predicate hides legitimate records from a service identity. Effective row access can differ across users and automation identities.

D:

A T-SQL load fails on two unknown nonnumeric identifiers among millions of rows. Targeted safe-conversion diagnostics locate failing source rows without corrupting valid IDs.

Question 692

A warehouse SQL engineer investigates failed joins and transformations. The engineer has established the following constraint: a T-SQL load fails on two unknown nonnumeric identifiers among millions of rows. Which action should the team take next?

  1. Identify invalid values with TRY_CONVERT and quarantine the offending records
  2. Move predicates to the intended pre/postaggregation stage and test output
  3. Test the predicate under the actual execution principal and correct authorized grants
  4. Use explicit schema-qualified table references and validate context

Explanation

Correct Answer

A:

Identify invalid values with TRY_CONVERT and quarantine the offending records. Targeted safe-conversion diagnostics locate failing source rows without corrupting valid IDs.

Incorrect Answers

B:

A GROUP BY result differs from expected totals due to misplaced WHERE filters. WHERE and HAVING apply at different query-processing stages.

C:

A new row-level security predicate hides legitimate records from a service identity. Effective row access can differ across users and automation identities.

D:

An UPDATE targets the wrong schema because object names are unqualified. Schema qualification avoids accidental resolution.

Question 693

A warehouse SQL engineer investigates failed joins and transformations. During an operations handoff, engineers find that a JOIN multiplies fact rows after a dimension gains duplicates. Which approach best satisfies this requirement?

  1. Use explicit schema-qualified table references and validate context
  2. Move predicates to the intended pre/postaggregation stage and test output
  3. Restore one relevant dimension row per join key and intended time period
  4. Identify invalid values with TRY_CONVERT and quarantine the offending records

Explanation

Correct Answer

C:

Restore one relevant dimension row per join key and intended time period. Cardinality errors affect semantics and performance.

Incorrect Answers

A:

An UPDATE targets the wrong schema because object names are unqualified. Schema qualification avoids accidental resolution.

B:

A GROUP BY result differs from expected totals due to misplaced WHERE filters. WHERE and HAVING apply at different query-processing stages.

D:

A T-SQL load fails on two unknown nonnumeric identifiers among millions of rows. Targeted safe-conversion diagnostics locate failing source rows without corrupting valid IDs.

Question 694

A warehouse SQL engineer investigates failed joins and transformations. The team observes that a GROUP BY result differs from expected totals due to misplaced WHERE filters. Which corrective action addresses the root cause?

  1. Move predicates to the intended pre/postaggregation stage and test output
  2. Restore one relevant dimension row per join key and intended time period
  3. Use explicit schema-qualified table references and validate context
  4. Test the predicate under the actual execution principal and correct authorized grants

Explanation

Correct Answer

A:

Move predicates to the intended pre/postaggregation stage and test output. WHERE and HAVING apply at different query-processing stages.

Incorrect Answers

B:

A JOIN multiplies fact rows after a dimension gains duplicates. Cardinality errors affect semantics and performance.

C:

An UPDATE targets the wrong schema because object names are unqualified. Schema qualification avoids accidental resolution.

D:

A new row-level security predicate hides legitimate records from a service identity. Effective row access can differ across users and automation identities.

Question 695

A warehouse SQL engineer investigates failed joins and transformations. The implementation review confirms that a new row-level security predicate hides legitimate records from a service identity. What should the administrator implement or verify?

  1. Test the predicate under the actual execution principal and correct authorized grants
  2. Use explicit schema-qualified table references and validate context
  3. Identify invalid values with TRY_CONVERT and quarantine the offending records
  4. Move predicates to the intended pre/postaggregation stage and test output

Explanation

Correct Answer

A:

Test the predicate under the actual execution principal and correct authorized grants. Effective row access can differ across users and automation identities.

Incorrect Answers

B:

An UPDATE targets the wrong schema because object names are unqualified. Schema qualification avoids accidental resolution.

C:

A T-SQL load fails on two unknown nonnumeric identifiers among millions of rows. Targeted safe-conversion diagnostics locate failing source rows without corrupting valid IDs.

D:

A GROUP BY result differs from expected totals due to misplaced WHERE filters. WHERE and HAVING apply at different query-processing stages.

Question 696

A Fabric admin investigates jobs failing under constrained capacity. A scheduled execution exposes this issue: Spark jobs fail at busy hours while idle periods work normally. Which approach best satisfies this requirement?

  1. Limit retries and concurrency with appropriate backoff
  2. Correlate executor failures and admission delays with capacity metrics
  3. Examine query plan costs, concurrent demand and capacity utilization
  4. Examine source-specific HTTP or database throttling telemetry

Explanation

Correct Answer

B:

Correlate executor failures and admission delays with capacity metrics. Saturation may be transient rather than a code defect.

Incorrect Answers

A:

A pipeline retry policy causes dozens of simultaneous requests after an outage. Retry storms amplify capacity pressure.

C:

Warehouse query timeouts spike when many scans overlap. Shared resource contention affects query latency.

D:

A Fabric capacity is healthy but an external source throttles extraction. External service limits are not resolved solely by increasing Fabric capacity.

Question 697

A Fabric admin investigates jobs failing under constrained capacity. Data validation establishes that a pipeline retry policy causes dozens of simultaneous requests after an outage. Which corrective action addresses the root cause?

  1. Check ingest throughput, compute pressure and destination limits
  2. Examine query plan costs, concurrent demand and capacity utilization
  3. Correlate executor failures and admission delays with capacity metrics
  4. Limit retries and concurrency with appropriate backoff

Explanation

Correct Answer

D:

Limit retries and concurrency with appropriate backoff. Retry storms amplify capacity pressure.

Incorrect Answers

A:

An Eventhouse backlog grows faster than consumers can process events. Sustained arrival rates can exceed provisioned processing capacity.

B:

Warehouse query timeouts spike when many scans overlap. Shared resource contention affects query latency.

C:

Spark jobs fail at busy hours while idle periods work normally. Saturation may be transient rather than a code defect.

Question 698

A Fabric admin investigates jobs failing under constrained capacity. The production incident report states that Warehouse query timeouts spike when many scans overlap. What should the administrator implement or verify?

  1. Correlate executor failures and admission delays with capacity metrics
  2. Limit retries and concurrency with appropriate backoff
  3. Examine source-specific HTTP or database throttling telemetry
  4. Examine query plan costs, concurrent demand and capacity utilization

Explanation

Correct Answer

D:

Examine query plan costs, concurrent demand and capacity utilization. Shared resource contention affects query latency.

Incorrect Answers

A:

Spark jobs fail at busy hours while idle periods work normally. Saturation may be transient rather than a code defect.

B:

A pipeline retry policy causes dozens of simultaneous requests after an outage. Retry storms amplify capacity pressure.

C:

A Fabric capacity is healthy but an external source throttles extraction. External service limits are not resolved solely by increasing Fabric capacity.

Question 699

A Fabric admin investigates jobs failing under constrained capacity. A postdeployment check reveals that an Eventhouse backlog grows faster than consumers can process events. Which option directly handles this observed condition?

  1. Examine query plan costs, concurrent demand and capacity utilization
  2. Examine source-specific HTTP or database throttling telemetry
  3. Check ingest throughput, compute pressure and destination limits
  4. Correlate executor failures and admission delays with capacity metrics

Explanation

Correct Answer

C:

Check ingest throughput, compute pressure and destination limits. Sustained arrival rates can exceed provisioned processing capacity.

Incorrect Answers

A:

Warehouse query timeouts spike when many scans overlap. Shared resource contention affects query latency.

B:

A Fabric capacity is healthy but an external source throttles extraction. External service limits are not resolved solely by increasing Fabric capacity.

D:

Spark jobs fail at busy hours while idle periods work normally. Saturation may be transient rather than a code defect.

Question 700

A Fabric admin investigates jobs failing under constrained capacity. The current environment exhibits the following problem: a Fabric capacity is healthy but an external source throttles extraction. What is the most defensible next action?

  1. Correlate executor failures and admission delays with capacity metrics
  2. Examine query plan costs, concurrent demand and capacity utilization
  3. Check ingest throughput, compute pressure and destination limits
  4. Examine source-specific HTTP or database throttling telemetry

Explanation

Correct Answer

D:

Examine source-specific HTTP or database throttling telemetry. External service limits are not resolved solely by increasing Fabric capacity.

Incorrect Answers

A:

Spark jobs fail at busy hours while idle periods work normally. Saturation may be transient rather than a code defect.

B:

Warehouse query timeouts spike when many scans overlap. Shared resource contention affects query latency.

C:

An Eventhouse backlog grows faster than consumers can process events. Sustained arrival rates can exceed provisioned processing capacity.