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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 60

Question 590

CSV amounts and dates are strings, but the curated Delta schema requires numeric and timestamp types. What should the engineer check to confirm that the intended behavior was achieved?

  1. The curated Delta table reflects tested joins and rejected parse cases.
  2. Destination schema is numeric and test totals calculate correctly.
  3. The Delta schema and sample values use correct data types.
  4. Spark and SQL read matching registered Delta records.

Explanation

Correct Answer

C:

Value and schema checks validate parsing. This observation directly tests the expected outcome.

Incorrect Answers

A:

Correct processed and rejected rows prove execution.

B:

Both schema and arithmetic verify the repair.

D:

Both engines retrieving equivalent rows confirms cross-engine availability.

Question 591

A dataflow refresh is triggered as part of a nightly pipeline but must finish before downstream notebook processing. Which observation most directly verifies the intended outcome after the appropriate action?

  1. The activity input differs per iteration and matches the expected table names.
  2. The notebook starts after dataflow completion according to activity timestamps.
  3. Run history shows the Copy and Notebook activity dependencies and correct failure path.
  4. The two notebook activity time intervals overlap during a successful run.

Explanation

Correct Answer

B:

Timestamp ordering validates the expected handoff. This observation directly tests the expected outcome.

Incorrect Answers

A:

Run input values demonstrate correct expression evaluation.

C:

Activity-level history confirms the designed control flow, not just that a notebook exists.

D:

Overlap and shared prerequisite completion verify parallel scheduling.

Question 592

Consider this Microsoft Fabric case: A streaming Delta sink receives repeated messages carrying the same business event ID. What measured result demonstrates that the requirement is satisfied?

  1. An intentionally replayed event ID does not increase the curated distinct event count.
  2. A new event appears promptly in the native KQL table and can be filtered.
  3. One event is observed in each intended sink with consistent identifiers.
  4. An injected restart does not duplicate committed business events.

Explanation

Correct Answer

A:

Controlled duplicate injection validates deduplication. This observation directly tests the expected outcome.

Incorrect Answers

B:

Native ingestion evidence verifies local queryability.

C:

Cross-destination correspondence validates fan-out. That observation may be useful elsewhere, but it does not directly confirm the expected evidence in the case: An intentionally replayed event ID does not increase the curated distinct event count.

D:

Replay invariance validates restart safety.

Question 593

Another workspace owns a trusted Delta table, and duplicate physical storage is prohibited. Which postchange result provides the strongest validation of success?

  1. Consumers query current source rows through the shortcut.
  2. Committed versions show consistent data with no partial corrupt writes.
  3. Counts per date-channel pair reconcile with source rows.
  4. All input rows are accounted for across both outputs.

Explanation

Correct Answer

A:

No independent physical copy and matching data validate virtualization. This observation directly tests the expected outcome.

Incorrect Answers

B:

Transaction history and row checks demonstrate integrity.

C:

Multi-key counts validate grouping. That observation may be useful elsewhere, but it does not directly confirm the expected evidence in the case: Consumers query current source rows through the shortcut.

D:

Conservation and rejection codes prove handling.

Question 594

A high-volume stream should be persisted for real-time analytics rather than continuously reread remote Parquet files. Which observation most directly verifies the intended outcome after the appropriate action?

  1. Recent incoming events are available in Eventhouse with expected ingestion freshness.
  2. Known events contribute to the expected overlapping window outputs.
  3. Fresh sample events reach the Eventhouse table and are queryable.
  4. New source events produce transformed target rows with expected field values.

Explanation

Correct Answer

A:

Direct event availability verifies the hot path. This observation directly tests the expected outcome.

Incorrect Answers

B:

Window memberships validate hop and duration.

C:

Event-to-table latency and content validate the route.

D:

Ingested target output validates policy execution.

Question 595

A Spark DataFrame job raises an unresolved-column AnalysisException after an upstream schema rename. Which observation most directly verifies the intended outcome after the appropriate action?

  1. The revised query resolves and returns the intended status values.
  2. The logical plan resolves every intended column and sample output is correct.
  3. Old and new supported payload samples produce correctly mapped output columns.
  4. A test event reaches the correct destination table without authorization errors.

Explanation

Correct Answer

B:

Schema resolution and data validation confirm repair. This observation directly tests the expected outcome.

Incorrect Answers

A:

Schema inspection and output correctness validate repair.

C:

Schema-generation tests validate parsing. That observation may be useful elsewhere, but it does not directly confirm the expected evidence in the case: The logical plan resolves every intended column and sample output is correct.

D:

Destination counter and stored row confirm access.

Question 596

A semantic model that serves reports appears stale despite yesterday's scheduled refresh. What should the engineer check to confirm that the intended behavior was achieved?

  1. The missing file causes a freshness alert despite other successful runs.
  2. Source and target measures reconcile at the required grouping grain.
  3. The last successful refresh is recent and report measures reflect that timestamp.
  4. The relevant refresh record has a completed status and corresponding new destination data.

Explanation

Correct Answer

C:

Successful completion plus data recency confirms freshness. This observation directly tests the expected outcome.

Incorrect Answers

A:

Negative input testing validates the detection.

B:

Business checks prevent false successful releases.

D:

Both execution status and data freshness validate success.

Question 597

A streaming alert should fire only when a rolling error rate exceeds a threshold for several minutes. Which observation most directly verifies the intended outcome after the appropriate action?

  1. Sustained high-rate fixtures trigger while isolated errors do not.
  2. The slow stage appears with disproportionately high execution duration.
  3. Errors align with the change time and clear after credential repair.
  4. The most recent successful timestamp excludes failed attempts.

Explanation

Correct Answer

A:

Controlled event sequences validate the intended threshold. This observation directly tests the expected outcome.

Incorrect Answers

B:

Granular timing identifies the actual hot spot.

C:

Temporal evidence confirms the operational cause.

D:

Accurate freshness uses completed valid refreshes.

Question 598

Spark join data exhibits runtime skew and adaptive execution is available. Which postchange result provides the strongest validation of success?

  1. The execution plan scans only relevant date partitions.
  2. Adaptive plan shows skew handling and less straggler delay.
  3. The plan joins fewer fact rows while results match.
  4. Physical plan uses broadcast and shuffle bytes decrease.

Explanation

Correct Answer

B:

Plan diagnostics prove runtime adaptation. This observation directly tests the expected outcome.

Incorrect Answers

A:

Pruned partitions verify effectiveness. That observation may be useful elsewhere, but it does not directly confirm the expected evidence in the case: Adaptive plan shows skew handling and less straggler delay.

C:

Rows and output parity confirm optimization.

D:

Plan and bytes verify the mechanism.

Question 599

Consider this Microsoft Fabric case: Modelers mainly use T-SQL views and relational joins over structured enterprise facts. What measured result demonstrates that the requirement is satisfied?

  1. Known products get correct categories and unmatched keys follow policy.
  2. The required T-SQL objects and relational queries execute correctly.
  3. Destination schema is numeric and test totals calculate correctly.
  4. Listing and reading the source objects works through the shortcut.

Explanation

Correct Answer

B:

Working joins validate the store against SQL requirements. This observation directly tests the expected outcome.

Incorrect Answers

A:

Sample joins and unmatched handling prove accuracy.

C:

Both schema and arithmetic verify the repair.

D:

Target content must track source objects.

Question 600

A CRM source permits updates to historical customer records and exposes a last-modified timestamp. What should the engineer check to confirm that the intended behavior was achieved?

  1. Current lookup returns one customer while time-travel queries return the correct older states.
  2. A modified existing customer changes one target row without creating a duplicate customer.
  3. Queries for dates before and after the change resolve to different dimension versions.
  4. The Fabric destination matches the authorized source snapshot by expected keys and record counts.

Explanation

Correct Answer

B:

Matched row identity and updated values prove correct upsert behavior. This observation directly tests the expected outcome.

Incorrect Answers

A:

Both use cases demonstrate intentional modeling rather than accidental duplication.

C:

Point-in-time joins verify that history was preserved.

D:

Baseline reconciliation verifies completeness rather than merely a successful job run.