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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 7

Question 60

A Fabric workspace is connected to Git for collaborative data engineering. The current environment exhibits the following problem: pulling repository updates would overwrite local workspace modifications. Which approach best satisfies this requirement?

  1. Review conflicts and commit or discard workspace changes deliberately before update
  2. Keep data content in governed storage and version the supported item definitions in Git
  3. Commit the supported item changes from the workspace to the connected repository
  4. Verify the connected branch and repository mapping before synchronization

Explanation

Correct Answer

A:

Review conflicts and commit or discard workspace changes deliberately before update. Source control synchronization requires reconciling divergent states.

Incorrect Answers

B:

A generated dataset is expected to be versioned alongside notebook code. Git integration is not a general backup of OneLake dataset contents.

C:

A workspace item changed but the repository still shows its earlier version. Git integration tracks supported item definitions only after synchronization.

D:

A developer syncs an unrelated Git branch into production accidentally. Workspace Git operations are scoped to an explicit repository branch.

Question 61

An analytics team promotes Fabric artifacts through test and production workspaces. An acceptance test shows that a tested notebook changes a hard-coded workspace ID when promoted. Which approach best satisfies this requirement?

  1. Restore a known-good item definition through controlled version/deployment workflow
  2. Parameterize or remap environment-specific workspace and Lakehouse references
  3. Review the supported item dependency relationships and deploy prerequisites together
  4. Require reviewed commits and controlled deployment pipeline promotion

Explanation

Correct Answer

B:

Parameterize or remap environment-specific workspace and Lakehouse references. Target identifiers often differ even when the item definition is equivalent.

Incorrect Answers

A:

A release must be rolled back after a defective notebook update. Versioned source enables auditable rollback of deployed definitions.

C:

A production deployment fails because required dependencies were not deployed. Downstream execution needs the referenced items available in the target stage.

D:

Developers deploy directly from an unreviewed branch to production. Code review and stage gates protect the production item state.

Question 62

An analytics team promotes Fabric artifacts through test and production workspaces. The engineer has established the following constraint: developers deploy directly from an unreviewed branch to production. Which corrective action addresses the root cause?

  1. Parameterize or remap environment-specific workspace and Lakehouse references
  2. Require reviewed commits and controlled deployment pipeline promotion
  3. Restore a known-good item definition through controlled version/deployment workflow
  4. Compare deployment-stage differences before selecting promoted items

Explanation

Correct Answer

B:

Require reviewed commits and controlled deployment pipeline promotion. Code review and stage gates protect the production item state.

Incorrect Answers

A:

A tested notebook changes a hard-coded workspace ID when promoted. Target identifiers often differ even when the item definition is equivalent.

C:

A release must be rolled back after a defective notebook update. Versioned source enables auditable rollback of deployed definitions.

D:

A deployment pipeline shows items as different but the team does not know which changed. Deployment diff prevents overwriting unrelated target changes.

Question 63

An analytics team promotes Fabric artifacts through test and production workspaces. During an operations handoff, engineers find that a deployment pipeline shows items as different but the team does not know which changed. What should the administrator implement or verify?

  1. Restore a known-good item definition through controlled version/deployment workflow
  2. Require reviewed commits and controlled deployment pipeline promotion
  3. Review the supported item dependency relationships and deploy prerequisites together
  4. Compare deployment-stage differences before selecting promoted items

Explanation

Correct Answer

D:

Compare deployment-stage differences before selecting promoted items. Deployment diff prevents overwriting unrelated target changes.

Incorrect Answers

A:

A release must be rolled back after a defective notebook update. Versioned source enables auditable rollback of deployed definitions.

B:

Developers deploy directly from an unreviewed branch to production. Code review and stage gates protect the production item state.

C:

A production deployment fails because required dependencies were not deployed. Downstream execution needs the referenced items available in the target stage.

Question 64

An analytics team promotes Fabric artifacts through test and production workspaces. The team observes that a production deployment fails because required dependencies were not deployed. Which option directly handles this observed condition?

  1. Require reviewed commits and controlled deployment pipeline promotion
  2. Compare deployment-stage differences before selecting promoted items
  3. Restore a known-good item definition through controlled version/deployment workflow
  4. Review the supported item dependency relationships and deploy prerequisites together

Explanation

Correct Answer

D:

Review the supported item dependency relationships and deploy prerequisites together. Downstream execution needs the referenced items available in the target stage.

Incorrect Answers

A:

Developers deploy directly from an unreviewed branch to production. Code review and stage gates protect the production item state.

B:

A deployment pipeline shows items as different but the team does not know which changed. Deployment diff prevents overwriting unrelated target changes.

C:

A release must be rolled back after a defective notebook update. Versioned source enables auditable rollback of deployed definitions.

Question 65

An analytics team promotes Fabric artifacts through test and production workspaces. The implementation review confirms that a release must be rolled back after a defective notebook update. What is the most defensible next action?

  1. Parameterize or remap environment-specific workspace and Lakehouse references
  2. Compare deployment-stage differences before selecting promoted items
  3. Require reviewed commits and controlled deployment pipeline promotion
  4. Restore a known-good item definition through controlled version/deployment workflow

Explanation

Correct Answer

D:

Restore a known-good item definition through controlled version/deployment workflow. Versioned source enables auditable rollback of deployed definitions.

Incorrect Answers

A:

A tested notebook changes a hard-coded workspace ID when promoted. Target identifiers often differ even when the item definition is equivalent.

B:

A deployment pipeline shows items as different but the team does not know which changed. Deployment diff prevents overwriting unrelated target changes.

C:

Developers deploy directly from an unreviewed branch to production. Code review and stage gates protect the production item state.

Question 66

A Fabric warehouse team uses database projects for schema source control. A scheduled execution exposes this issue: a warehouse table definition differs between production and Git. Which technical choice fits this evidence?

  1. Include reviewed SQL changes in the connected repository and build artifacts
  2. Review the schema comparison and deployment script before applying changes
  3. Represent supported database schema objects in a versioned SQL database project
  4. Compare deployed warehouse objects with the reviewed project baseline

Explanation

Correct Answer

C:

Represent supported database schema objects in a versioned SQL database project. Schema-as-code enables repeatable review and promotion.

Incorrect Answers

A:

A developer adds a local SQL script but never checks it in. A local-only file does not become part of the controlled release.

B:

A new table change could unintentionally drop production columns. Database project publishing can contain destructive object changes.

D:

A production database project deployment has unexpected schema drift. Drift analysis identifies uncontrolled changes outside approved source.

Question 67

A Fabric warehouse team uses database projects for schema source control. Data validation establishes that a new table change could unintentionally drop production columns. Which step preserves the intended data behavior?

  1. Represent supported database schema objects in a versioned SQL database project
  2. Include reviewed SQL changes in the connected repository and build artifacts
  3. Review the schema comparison and deployment script before applying changes
  4. Compare deployed warehouse objects with the reviewed project baseline

Explanation

Correct Answer

C:

Review the schema comparison and deployment script before applying changes. Database project publishing can contain destructive object changes.

Incorrect Answers

A:

A warehouse table definition differs between production and Git. Schema-as-code enables repeatable review and promotion.

B:

A developer adds a local SQL script but never checks it in. A local-only file does not become part of the controlled release.

D:

A production database project deployment has unexpected schema drift. Drift analysis identifies uncontrolled changes outside approved source.

Question 68

A Fabric warehouse team uses database projects for schema source control. The production incident report states that a pipeline's T-SQL scripts run before prerequisite warehouse tables exist. Which change most directly resolves this failure?

  1. Deploy the required schema migration before dependent data loads
  2. Represent supported database schema objects in a versioned SQL database project
  3. Include reviewed SQL changes in the connected repository and build artifacts
  4. Compare deployed warehouse objects with the reviewed project baseline

Explanation

Correct Answer

A:

Deploy the required schema migration before dependent data loads. Execution ordering must satisfy database object dependencies.

Incorrect Answers

B:

A warehouse table definition differs between production and Git. Schema-as-code enables repeatable review and promotion.

C:

A developer adds a local SQL script but never checks it in. A local-only file does not become part of the controlled release.

D:

A production database project deployment has unexpected schema drift. Drift analysis identifies uncontrolled changes outside approved source.

Question 69

A Fabric warehouse team uses database projects for schema source control. A postdeployment check reveals that a developer adds a local SQL script but never checks it in. What is the best engineering response?

  1. Include reviewed SQL changes in the connected repository and build artifacts
  2. Deploy the required schema migration before dependent data loads
  3. Review the schema comparison and deployment script before applying changes
  4. Compare deployed warehouse objects with the reviewed project baseline

Explanation

Correct Answer

A:

Include reviewed SQL changes in the connected repository and build artifacts. A local-only file does not become part of the controlled release.

Incorrect Answers

B:

A pipeline's T-SQL scripts run before prerequisite warehouse tables exist. Execution ordering must satisfy database object dependencies.

C:

A new table change could unintentionally drop production columns. Database project publishing can contain destructive object changes.

D:

A production database project deployment has unexpected schema drift. Drift analysis identifies uncontrolled changes outside approved source.

Question 70

A Fabric warehouse team uses database projects for schema source control. The current environment exhibits the following problem: a production database project deployment has unexpected schema drift. Which action should the team take next?

  1. Compare deployed warehouse objects with the reviewed project baseline
  2. Include reviewed SQL changes in the connected repository and build artifacts
  3. Review the schema comparison and deployment script before applying changes
  4. Represent supported database schema objects in a versioned SQL database project

Explanation

Correct Answer

A:

Compare deployed warehouse objects with the reviewed project baseline. Drift analysis identifies uncontrolled changes outside approved source.

Incorrect Answers

B:

A developer adds a local SQL script but never checks it in. A local-only file does not become part of the controlled release.

C:

A new table change could unintentionally drop production columns. Database project publishing can contain destructive object changes.

D:

A warehouse table definition differs between production and Git. Schema-as-code enables repeatable review and promotion.