mcAfee Secure Website
23

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

DP-700 Training Materials $25.00
Pass4sure Q&A Sample #1 Pass4sure Q&A Sample #2 Pass4sure Q&A Sample #3 Pass4sure Q&A Sample #4 Pass4sure Q&A Sample #5 Pass4sure Q&A Sample #6 Pass4sure Q&A Sample #7 Pass4sure Q&A Sample #8 Pass4sure Q&A Sample #9 Pass4sure Q&A Sample #10

Reliable & Actual Study Materials for DP-700 Exam Success

The Latest DP-700 Exam Questions as Experienced in the Actual Test!

  • 24
    Questions & Answers

    DP-700 Questions & Answers

    160 Questions & Answers

    Includes questions types found on actual exam such as drag and drop, simulation, type in, and fill in the blank.

  • 25
    DP-700 Video Course

    DP-700 Training Course

    160 Video Lectures

    Based on Real Life Scenarios which you will encounter in exam and learn by working with real equipment.

exam =32

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

Guarantee

Satisfaction Guaranteed

Pass4sure has a remarkable Microsoft Candidate Success record. We're confident of our products and provide no hassle product exchange. That's how confident we are!

99.3% Pass Rate
Total Cost: $164.98
Bundle Price: $139.98

Purchase Individually

  • exam =34
    Questions & Answers

    Questions & Answers

    160 Questions

    $124.99
    exam =35
  • exam =37
    DP-700 Video Course

    Training Course

    160 Video Lectures

    $39.99

Microsoft DP-700 Practice Test 20

Question 190

An organization governs data ownership, metadata, and discovery. The current environment exhibits the following problem: a data steward wants proof that an item owner changed classification. Which approach best satisfies this requirement?

  1. Assign and document ownership under the appropriate workspace or domain governance process
  2. Consult retained Fabric audit activity around label or ownership operations
  3. Diagnose item discovery separately from OneLake/SQL data permission grants
  4. Update the governed metadata alongside the item and schema change

Explanation

Correct Answer

B:

Consult retained Fabric audit activity around label or ownership operations. Audit evidence helps attribute governance changes.

Incorrect Answers

A:

New source tables lack a clear accountable data steward. Stewardship is necessary for trustworthy catalog maintenance.

C:

A confidential table is searchable in catalog but inaccessible to intended readers. Finding an item and reading its contents are different privileges.

D:

An internal catalog contains stale table descriptions after a schema rollout. Discovery metadata must track the current data contract.

Question 191

A Fabric security review validates actual effective permissions before launch. An acceptance test shows that an external shortcut source identity has excessive bucket permissions. Which technical choice fits this evidence?

  1. Validate the semantic model's source identity mode and data security behavior
  2. Scope the external connection credential to only approved source paths
  3. Review group membership and tighten effective OneLake roles on the protected tables
  4. Test with the actual Viewer permissions and applicable OneLake reader roles

Explanation

Correct Answer

B:

Scope the external connection credential to only approved source paths. A delegated credential is a real authority boundary.

Incorrect Answers

A:

A report uses a semantic model whose query identity is different from the viewing user. Consumer filtering depends on how the model accesses the source.

C:

A sensitive Lakehouse is shared with a broad Entra group. Group grants can expose data to unexpected members.

D:

A security tester uses an Admin account and concludes Viewer restrictions are broken. Privileged workspace roles have broader authoring/data rights.

Question 192

A Fabric security review validates actual effective permissions before launch. The engineer has established the following constraint: a sensitive Lakehouse is shared with a broad Entra group. Which step preserves the intended data behavior?

  1. Run positive and negative data-access tests as representative target-stage users
  2. Scope the external connection credential to only approved source paths
  3. Test with the actual Viewer permissions and applicable OneLake reader roles
  4. Review group membership and tighten effective OneLake roles on the protected tables

Explanation

Correct Answer

D:

Review group membership and tighten effective OneLake roles on the protected tables. Group grants can expose data to unexpected members.

Incorrect Answers

A:

A release promotes new SQL tables without rechecking row-security policies. Tested access results validate intended security across deployments.

B:

An external shortcut source identity has excessive bucket permissions. A delegated credential is a real authority boundary.

C:

A security tester uses an Admin account and concludes Viewer restrictions are broken. Privileged workspace roles have broader authoring/data rights.

Question 193

A Fabric security review validates actual effective permissions before launch. During an operations handoff, engineers find that a report uses a semantic model whose query identity is different from the viewing user. Which change most directly resolves this failure?

  1. Review group membership and tighten effective OneLake roles on the protected tables
  2. Scope the external connection credential to only approved source paths
  3. Validate the semantic model's source identity mode and data security behavior
  4. Run positive and negative data-access tests as representative target-stage users

Explanation

Correct Answer

C:

Validate the semantic model's source identity mode and data security behavior. Consumer filtering depends on how the model accesses the source.

Incorrect Answers

A:

A sensitive Lakehouse is shared with a broad Entra group. Group grants can expose data to unexpected members.

B:

An external shortcut source identity has excessive bucket permissions. A delegated credential is a real authority boundary.

D:

A release promotes new SQL tables without rechecking row-security policies. Tested access results validate intended security across deployments.

Question 194

A Fabric security review validates actual effective permissions before launch. The team observes that a security tester uses an Admin account and concludes Viewer restrictions are broken. What is the best engineering response?

  1. Review group membership and tighten effective OneLake roles on the protected tables
  2. Validate the semantic model's source identity mode and data security behavior
  3. Run positive and negative data-access tests as representative target-stage users
  4. Test with the actual Viewer permissions and applicable OneLake reader roles

Explanation

Correct Answer

D:

Test with the actual Viewer permissions and applicable OneLake reader roles. Privileged workspace roles have broader authoring/data rights.

Incorrect Answers

A:

A sensitive Lakehouse is shared with a broad Entra group. Group grants can expose data to unexpected members.

B:

A report uses a semantic model whose query identity is different from the viewing user. Consumer filtering depends on how the model accesses the source.

C:

A release promotes new SQL tables without rechecking row-security policies. Tested access results validate intended security across deployments.

Question 195

A Fabric security review validates actual effective permissions before launch. The implementation review confirms that a release promotes new SQL tables without rechecking row-security policies. Which action should the team take next?

  1. Scope the external connection credential to only approved source paths
  2. Run positive and negative data-access tests as representative target-stage users
  3. Validate the semantic model's source identity mode and data security behavior
  4. Test with the actual Viewer permissions and applicable OneLake reader roles

Explanation

Correct Answer

B:

Run positive and negative data-access tests as representative target-stage users. Tested access results validate intended security across deployments.

Incorrect Answers

A:

An external shortcut source identity has excessive bucket permissions. A delegated credential is a real authority boundary.

C:

A report uses a semantic model whose query identity is different from the viewing user. Consumer filtering depends on how the model accesses the source.

D:

A security tester uses an Admin account and concludes Viewer restrictions are broken. Privileged workspace roles have broader authoring/data rights.

Question 196

A Fabric data engineer must choose the right implementation tool for recurring work. A scheduled execution exposes this issue: business analysts require low-code joins and filters in a managed transformation. Which step preserves the intended data behavior?

  1. Choose a suitable Copy activity or Copy job for the supported source and sink
  2. Use Dataflow Gen2 with Power Query transformations and managed destination
  3. Use a Data Factory pipeline with explicit activity dependencies
  4. Orchestrate the notebook within a pipeline or suitable scheduler

Explanation

Correct Answer

B:

Use Dataflow Gen2 with Power Query transformations and managed destination. Dataflows support repeatable low-code ETL steps.

Incorrect Answers

A:

A job only needs to move data efficiently without elaborate custom transformation. Data movement is distinct from analytical transformation logic.

C:

Several dependent copies and notebook runs must execute in order. Pipelines coordinate heterogeneous data tasks.

D:

A stakeholder assumes a notebook alone schedules and retries an entire multi-item workflow. Running code and managing cross-item dependencies are different concerns.

Question 197

A Fabric data engineer must choose the right implementation tool for recurring work. Data validation establishes that engineers need Python and Spark distributed processing over large files. Which change most directly resolves this failure?

  1. Use Dataflow Gen2 with Power Query transformations and managed destination
  2. Orchestrate the notebook within a pipeline or suitable scheduler
  3. Use a Data Factory pipeline with explicit activity dependencies
  4. Use a Fabric notebook or Spark job definition for code-first transformations

Explanation

Correct Answer

D:

Use a Fabric notebook or Spark job definition for code-first transformations. Spark provides distributed data processing not equivalent to a simple copy.

Incorrect Answers

A:

Business analysts require low-code joins and filters in a managed transformation. Dataflows support repeatable low-code ETL steps.

B:

A stakeholder assumes a notebook alone schedules and retries an entire multi-item workflow. Running code and managing cross-item dependencies are different concerns.

C:

Several dependent copies and notebook runs must execute in order. Pipelines coordinate heterogeneous data tasks.

Question 198

A Fabric data engineer must choose the right implementation tool for recurring work. The production incident report states that several dependent copies and notebook runs must execute in order. What is the best engineering response?

  1. Use Dataflow Gen2 with Power Query transformations and managed destination
  2. Orchestrate the notebook within a pipeline or suitable scheduler
  3. Choose a suitable Copy activity or Copy job for the supported source and sink
  4. Use a Data Factory pipeline with explicit activity dependencies

Explanation

Correct Answer

D:

Use a Data Factory pipeline with explicit activity dependencies. Pipelines coordinate heterogeneous data tasks.

Incorrect Answers

A:

Business analysts require low-code joins and filters in a managed transformation. Dataflows support repeatable low-code ETL steps.

B:

A stakeholder assumes a notebook alone schedules and retries an entire multi-item workflow. Running code and managing cross-item dependencies are different concerns.

C:

A job only needs to move data efficiently without elaborate custom transformation. Data movement is distinct from analytical transformation logic.

Question 199

A Fabric data engineer must choose the right implementation tool for recurring work. A postdeployment check reveals that a job only needs to move data efficiently without elaborate custom transformation. Which action should the team take next?

  1. Use Dataflow Gen2 with Power Query transformations and managed destination
  2. Orchestrate the notebook within a pipeline or suitable scheduler
  3. Choose a suitable Copy activity or Copy job for the supported source and sink
  4. Use a Fabric notebook or Spark job definition for code-first transformations

Explanation

Correct Answer

C:

Choose a suitable Copy activity or Copy job for the supported source and sink. Data movement is distinct from analytical transformation logic.

Incorrect Answers

A:

Business analysts require low-code joins and filters in a managed transformation. Dataflows support repeatable low-code ETL steps.

B:

A stakeholder assumes a notebook alone schedules and retries an entire multi-item workflow. Running code and managing cross-item dependencies are different concerns.

D:

Engineers need Python and Spark distributed processing over large files. Spark provides distributed data processing not equivalent to a simple copy.

Question 200

A Fabric data engineer must choose the right implementation tool for recurring work. The current environment exhibits the following problem: a stakeholder assumes a notebook alone schedules and retries an entire multi-item workflow. Which approach best satisfies this requirement?

  1. Orchestrate the notebook within a pipeline or suitable scheduler
  2. Use a Data Factory pipeline with explicit activity dependencies
  3. Choose a suitable Copy activity or Copy job for the supported source and sink
  4. Use a Fabric notebook or Spark job definition for code-first transformations

Explanation

Correct Answer

A:

Orchestrate the notebook within a pipeline or suitable scheduler. Running code and managing cross-item dependencies are different concerns.

Incorrect Answers

B:

Several dependent copies and notebook runs must execute in order. Pipelines coordinate heterogeneous data tasks.

C:

A job only needs to move data efficiently without elaborate custom transformation. Data movement is distinct from analytical transformation logic.

D:

Engineers need Python and Spark distributed processing over large files. Spark provides distributed data processing not equivalent to a simple copy.