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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 18

Question 170

A notebook raises ModuleNotFoundError for a package that works in another team workspace. What should the engineer implement first to satisfy the stated need?

  1. Attach and publish the environment containing the required compatible library.
  2. Fix the required source or target authorization rather than increasing retry count.
  3. Preserve the required precision by selecting an appropriate compatible sink numeric type.
  4. Rebind the notebook to the intended target-stage default lakehouse and resolve the path.

Explanation

Correct Answer

A:

Notebook sessions resolve available libraries from their effective environment.

Incorrect Answers

B:

Permission denial is not resolved by more attempts without changing access.

C:

Narrow integer types cannot represent decimal input without loss or failure.

D:

Notebook references depend on an effective lakehouse binding in each environment.

Question 171

In a Microsoft Fabric solution, supported operational database updates should appear in Fabric without nightly extraction scripts. Which configuration or implementation should the engineer choose?

  1. Create a pipeline Copy activity into the destination.
  2. Select a OneLake shortcut instead of database mirroring.
  3. Configure a supported mirrored database.
  4. Land the events in an Eventhouse KQL database.

Explanation

Correct Answer

C:

Mirroring propagates ongoing source changes into analytical tables.

Incorrect Answers

A:

Copy handles scalable source-to-target data movement.

B:

Shortcuts virtualize object access while mirroring replicates changes.

D:

Eventhouse supports high-throughput time-series ingestion and KQL.

Question 172

A deployed notebook must target the test lakehouse rather than a development lakehouse even when the workspace has a different default. Which engineering decision is most suitable for this specific situation?

  1. Configure an appropriate notebook deployment rule on the target stage.
  2. Update the Git-connected workspace from the repository branch.
  3. Use deployment pipeline dependency mapping for internal shortcut references.
  4. Use environment-specific deployment configuration while keeping one versioned database project.

Explanation

Correct Answer

A:

Target-stage deployment rules can override notebook bindings such as the default lakehouse.

Incorrect Answers

B:

Git update applies incoming committed definitions to the connected workspace.

C:

Internal shortcuts can be remapped to corresponding items across supported stages.

D:

Separating deployment settings from schema definitions maintains one canonical source model.

Question 173

A deployment creates an empty target lakehouse while notebooks continue pointing to an upstream lakehouse through dependency mapping. Which action best addresses the requirement?

  1. Inspect and correct dependency mapping independently of the newly created lakehouse.
  2. Deploy the reviewed SQL schema change rather than replacing warehouse data.
  3. Keep lakehouse data files in governed storage and version only supported lakehouse metadata in Git.
  4. Deploy lakehouse metadata while treating table data as separately managed.

Explanation

Correct Answer

A:

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

Incorrect Answers

B:

Schema definitions and physical data are distinct release concerns.

C:

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

D:

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

Question 174

Too many tiny Spark shuffle partitions create thousands of tasks for a small dataset. What should the engineer implement first to satisfy the stated need?

  1. Tune supported ingestion batching policy for the feed.
  2. Right-size executor resources in the attached environment.
  3. Tune shuffle partition count to match volume and resources.
  4. Apply supported liquid clustering on customer key.

Explanation

Correct Answer

C:

Excess tiny tasks add scheduling overhead. The result addresses the requirement stated in this case.

Incorrect Answers

A:

Suitable batching balances ingest overhead with freshness.

B:

Sufficient compatible executor memory can reduce spills and failures.

D:

Clustering improves locality without a directory for each value.

Question 175

Events from devices carry local timestamps from several time zones and must be comparable in a global stream. Which engineering decision is most suitable for this specific situation?

  1. Re-read a bounded overlap window and deduplicate or merge by business key.
  2. Define one consistent grain for the fact table before loading.
  3. Use event-time processing with a configured lateness or watermark policy.
  4. Normalize event timestamps to a consistent time basis such as UTC.

Explanation

Correct Answer

D:

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

Incorrect Answers

A:

An overlap interval guards against delayed visibility without duplicating accepted data.

B:

A declared grain ensures each row represents one kind of business event or aggregation.

C:

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

Question 176

Events can arrive up to six minutes out of order and a streaming aggregate must wait appropriately. Which engineering decision is most suitable for this specific situation?

  1. Base time-series grouping on the business event timestamp.
  2. Use a stateful streaming join with a valid event-time bound and watermark policy.
  3. Apply an event-time watermark that covers the accepted lateness policy.
  4. Use deduplication keyed on event ID within a defined streaming state policy.

Explanation

Correct Answer

C:

Watermarks bound the amount of late data retained in streaming state.

Incorrect Answers

A:

Event-time semantics reflect when the event occurred, not when ingestion received it.

B:

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

D:

Keyed streaming deduplication limits duplicate business contributions.

Question 177

In a Microsoft Fabric solution, malformed streaming JSON must be investigated without corrupting curated telemetry tables. Which configuration or implementation should the engineer choose?

  1. Route parse failures to an error or quarantine path with identifying metadata.
  2. Apply a stream filter or derived boolean expression on the temperature field.
  3. Create an Eventstream route into an Eventhouse KQL table.
  4. Use deduplication keyed on event ID within a defined streaming state policy.

Explanation

Correct Answer

A:

Separating invalid events preserves traceability and protects curated results.

Incorrect Answers

B:

Stream transformations can identify records meeting numerical conditions.

C:

Eventstream can ingest and route streaming data to a KQL destination.

D:

Keyed streaming deduplication limits duplicate business contributions.

Question 178

An engineer wants a reusable child pipeline to perform a standard audit step for several parent pipelines. Which engineering decision is most suitable for this specific situation?

  1. Expose the business date as a pipeline parameter and supply it at invocation.
  2. Inspect the pipeline's individual activity runs and their error outputs.
  3. Place the dataflow activity upstream of the notebook in the pipeline dependency graph.
  4. Invoke the reusable pipeline through an Execute Pipeline activity.

Explanation

Correct Answer

D:

Child pipelines allow shared orchestration logic without cloning all activities.

Incorrect Answers

A:

A runtime parameter separates job logic from each run's effective processing date.

B:

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

C:

Explicit dependencies prevent processing before upstream dataflow completion.

Question 179

A Dataflow Gen2 query step errors after source rows include nonnumeric text in a previously numeric field. What should the engineer implement first to satisfy the stated need?

  1. Use an appropriate target type and safe conversion with invalid-record handling.
  2. Handle conversion errors explicitly and route malformed values for review.
  3. Restore gateway availability or select a valid supported gateway connection.
  4. Inspect capacity concurrency and queueing before rewriting the notebooks.

Explanation

Correct Answer

B:

Power Query type conversion can fail when source values violate the expected type.

Incorrect Answers

A:

Unsafe casts fail when values cannot be represented in the target type.

C:

A gateway-dependent source requires an operational gateway path.

D:

Resource availability can delay execution independently of notebook correctness.

Question 180

In a Microsoft Fabric solution, a pipeline is called for multiple countries and needs its source path to vary without editing its JSON each time. Which configuration or implementation should the engineer choose?

  1. Configure failure notifications on the scheduled pipeline run.
  2. Define pipeline parameters and reference them with dynamic content expressions.
  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:

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

Incorrect Answers

A:

Scheduled pipelines support configured failure notifications distinct from manual invocation.

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.