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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 4

Question 30

A dataflow refresh is triggered as part of a nightly pipeline but must finish before downstream notebook processing. Which engineering decision is most suitable for this specific situation?

  1. Build a Fabric data pipeline with Copy and Notebook activities and failure handling.
  2. Invoke the reusable pipeline through an Execute Pipeline activity.
  3. Place both notebook activities on parallel branches after the staging success dependency.
  4. Place the dataflow activity upstream of the notebook in the pipeline dependency graph.

Explanation

Correct Answer

D:

Explicit dependencies prevent processing before upstream dataflow completion.

Incorrect Answers

A:

Pipelines orchestrate multi-activity ingestion and dependent jobs.

B:

Child pipelines allow shared orchestration logic without cloning all activities.

C:

Parallel branches enable independent work once common prerequisites are met.

Question 31

A warehouse table exposes sensitive salary data; analysts may query other columns but must not select Salary at all. Which engineering decision is most suitable for this specific situation?

  1. Use column-level access controls to deny the Salary column to analysts.
  2. Implement T-SQL row-level security with a filtering predicate and security policy.
  3. Apply SQL object-level permissions to that procedure.
  4. Apply column-level constraints in a read-only OneLake security role.

Explanation

Correct Answer

A:

Column-level security restricts permission to access specific columns rather than merely displaying masked values.

Incorrect Answers

B:

Row-level security restricts which records are returned based on the query context.

C:

Object-level security controls access to entire objects such as views or procedures.

D:

OneLake Read roles can constrain selected columns for the specified members.

Question 32

An Eventhouse KQL query repeatedly reads large external Delta tables through OneLake shortcuts. Which action best addresses the requirement?

  1. Adopt supported declarative liquid clustering.
  2. Tune supported ingestion batching policy for the feed.
  3. Enable supported query acceleration.
  4. Tune supported caching and ingestion settings around the hot window.

Explanation

Correct Answer

C:

Acceleration caches eligible external data for faster KQL queries.

Incorrect Answers

A:

Liquid clustering persists chosen columns in table metadata.

B:

Suitable batching balances ingest overhead with freshness.

D:

Keeping active data efficient reduces cold reads.

Question 33

A KQL dashboard needs the complete latest observation per sensor, not only the maximum timestamp column. Which action best addresses the requirement?

  1. Set the query acceleration policy's cache period to seven days.
  2. Use summarize arg_max(timestamp, *) by sensor_id.
  3. Base time-series grouping on the business event timestamp.
  4. Apply a stream filter or derived boolean expression on the temperature field.

Explanation

Correct Answer

B:

Arg_max selects the row associated with a maximum expression per group.

Incorrect Answers

A:

The policy controls a window of eligible external Delta data relative to modification time.

C:

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

D:

Stream transformations can identify records meeting numerical conditions.

Question 34

In a Microsoft Fabric solution, analysts need a continuous hourly series including intervals with no events, not only hours where rows exist. Which configuration or implementation should the engineer choose?

  1. Base time-series grouping on the business event timestamp.
  2. Apply an event-time watermark that covers the accepted lateness policy.
  3. Use KQL make-series with the intended time range and step.
  4. Use a stateful streaming join with a valid event-time bound and watermark policy.

Explanation

Correct Answer

C:

Make-series constructs regular time bins and can represent empty intervals.

Incorrect Answers

A:

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

B:

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

D:

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

Question 35

In a Microsoft Fabric solution, a Copy activity reaches a warehouse target but rejects records due to source and sink column-type incompatibility. Which configuration or implementation should the engineer choose?

  1. Refresh the source connection's authorized credentials and rerun the Copy activity.
  2. Correct the Copy mapping and type conversions for the affected columns.
  3. Preserve the required precision by selecting an appropriate compatible sink numeric type.
  4. Correct the Eventhouse ingestion mapping to the intended timestamp column and type.

Explanation

Correct Answer

B:

Data type mismatch occurs at mapping or insert even when connectivity succeeds.

Incorrect Answers

A:

Authentication failure occurs before data transfer when credentials are no longer valid.

C:

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

D:

Ingestion mapping aligns payload paths with typed target fields.

Question 36

In a Microsoft Fabric solution, sQL joins use incompatible key data types that require implicit conversion. Which configuration or implementation should the engineer choose?

  1. Normalize compatible join-key data types.
  2. Use a skew-aware join plan or carefully designed salting.
  3. Use a suitable broadcast join.
  4. Filter unwanted types before the destination.

Explanation

Correct Answer

A:

Conversions on join paths can increase query cost.

Incorrect Answers

B:

Redistribution prevents one worker from becoming a straggler.

C:

Broadcasting small lookup data can avoid shuffling the large fact.

D:

Earlier stream filtering reduces unnecessary downstream traffic.

Question 37

In a Microsoft Fabric solution, sensors publish continuous telemetry to a supported source, and investigators need near-real-time KQL queries. Which configuration or implementation should the engineer choose?

  1. Route parse failures to an error or quarantine path with identifying metadata.
  2. Create an Eventstream route into an Eventhouse KQL table.
  3. Create a suitable KQL materialized view for the frequently reused aggregation.
  4. Ingest events into an Eventhouse native table instead of querying only an external shortcut.

Explanation

Correct Answer

B:

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

Incorrect Answers

A:

Separating invalid events preserves traceability and protects curated results.

C:

Materialized views maintain precomputed results for supported KQL aggregation patterns.

D:

Native Eventhouse ingestion supports indexed real-time analytics over event records.

Question 38

An expensive warehouse query requires operator analysis without repeatedly running against production data. Which action best addresses the requirement?

  1. Investigate supported FORCE DISTRIBUTED PLAN after ordinary tuning.
  2. Inspect an estimated execution plan with supported SHOWPLAN tooling.
  3. Tune supported caching and ingestion settings around the hot window.
  4. Configure supported partitioned source reads and controlled parallelism.

Explanation

Correct Answer

B:

Estimated plans show likely operators before full execution.

Incorrect Answers

A:

A distributed hint may change plan topology for eligible queries.

C:

Keeping active data efficient reduces cold reads.

D:

Parallel partition reads can improve throughput if the source supports them.

Question 39

A streaming Delta sink receives repeated messages carrying the same business event ID. Which action best addresses the requirement?

  1. Add an Eventstream filter on event type before the destination.
  2. Use deduplication keyed on event ID within a defined streaming state policy.
  3. Apply an event-time watermark that covers the accepted lateness policy.
  4. Use a stateful streaming join with a valid event-time bound and watermark policy.

Explanation

Correct Answer

B:

Keyed streaming deduplication limits duplicate business contributions.

Incorrect Answers

A:

Eventstream transformations can route selected records according to event attributes.

C:

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

D:

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

Question 40

An Eventstream appears healthy but ingestion stopped shortly after a source connection rotated its credentials. Which engineering decision is most suitable for this specific situation?

  1. Compare run parameters, linked connection contexts, and activity outputs across environments.
  2. Correlate stream diagnostics with source connection errors at the credential rotation time.
  3. Configure an appropriate Fabric real-time alert through the supported alert experience.
  4. Check Eventhouse ingestion freshness and the dashboard query time range separately.

Explanation

Correct Answer

B:

Connection failures may stop ingestion while item metadata remains present.

Incorrect Answers

A:

Contextual run evidence isolates configuration drift.

C:

Alerts watch incoming query or event conditions without manually polling dashboards.

D:

A stale visualization may result from query filtering rather than ingestion failure.