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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 29

Question 280

Modelers mainly use T-SQL views and relational joins over structured enterprise facts. Which action best addresses the requirement?

  1. Choose a Fabric Warehouse for the SQL-first model.
  2. Choose a Fabric lakehouse for file-oriented analytical storage.
  3. Join facts to reference rows by stable product key.
  4. Run the logic in a Fabric PySpark notebook.

Explanation

Correct Answer

A:

Warehouse supports relational tables and T-SQL analytical workloads.

Incorrect Answers

B:

Lakehouses combine OneLake files, Spark Delta tables, and a SQL endpoint.

C:

Enrichment joins add trusted attributes from matching keys.

D:

Notebooks support custom distributed transformations and environments.

Question 281

A Warehouse T-SQL query fails due to a malformed JOIN syntax after an editing change. Which action best addresses the requirement?

  1. Correct the Copy mapping and type conversions for the affected columns.
  2. Correct the T-SQL syntax using the Warehouse-supported grammar.
  3. Inspect evaluated dynamic expressions and correct the runtime source path.
  4. Restore gateway availability or select a valid supported gateway connection.

Explanation

Correct Answer

B:

Invalid SQL grammar fails during parsing before meaningful execution.

Incorrect Answers

A:

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

C:

A wrong path can fail even when the connection itself is valid.

D:

A gateway-dependent source requires an operational gateway path.

Question 282

A warehouse fact-to-dimension join builds huge intermediate data before a selective predicate applies. Which action best addresses the requirement?

  1. Reduce the filtered set before a necessary global sort.
  2. Push the filter before the groupBy shuffle.
  3. Use a suitable broadcast join.
  4. Push selective filters before the expensive join.

Explanation

Correct Answer

D:

Earlier predicates reduce processed rows. The result addresses the requirement stated in this case.

Incorrect Answers

A:

Global sorting can trigger non-scalable processing.

B:

Earlier row reduction lowers shuffle volume.

C:

Broadcasting small lookup data can avoid shuffling the large fact.

Question 283

Some source changes reach the extraction endpoint late, with timestamps up to ten minutes behind ingestion time. Which action best addresses the requirement?

  1. Recompute or adjust affected aggregates using the changed underlying business keys.
  2. Re-read a bounded overlap window and deduplicate or merge by business key.
  3. Backfill only the missing business-date partition with idempotent processing.
  4. Deduplicate using the complete business key of transaction ID and line number.

Explanation

Correct Answer

B:

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

Incorrect Answers

A:

Corrections must flow into derived measures, not only the detail table.

C:

A targeted backfill repairs the gap without unnecessarily reloading unrelated dates.

D:

A composite key matches the actual record identity rather than a locally repeated attribute.

Question 284

A team needs to detect if pipeline runs exceed the 40-minute ingestion service-level objective. Which action best addresses the requirement?

  1. Aggregate pipeline run outcomes by date and failure type.
  2. Measure durations from recorded pipeline start and end timestamps and alert on the breached threshold.
  3. Introduce suppression or deduplication of recurring alerts for the incident key where supported.
  4. Monitor the expected source arrival or transfer event for the specific file.

Explanation

Correct Answer

B:

Run durations support reliable SLO assessment. The result addresses the requirement stated in this case.

Incorrect Answers

A:

Trend monitoring reveals recurrent errors not visible from a single run.

C:

Alert deduplication reduces repeat notifications without hiding a new incident.

D:

A targeted freshness condition detects missing inputs independently of other job success.

Question 285

In a Microsoft Fabric solution, a database team wants to review and version a Fabric Warehouse schema as code before deploying T-SQL changes. Which configuration or implementation should the engineer choose?

  1. Use a SQL database project containing the warehouse schema definitions.
  2. Retain the external shortcut target when promoting the lakehouse definition.
  3. Use the deployment pipeline stage comparison to review pending item changes.
  4. Review the Git changes and differences for the affected supported Fabric items.

Explanation

Correct Answer

A:

Database projects capture deployable SQL object definitions in source control.

Incorrect Answers

B:

External OneLake shortcut definitions keep their referenced external targets during supported deployment.

C:

Stage comparison identifies supported items that changed or are missing between stages.

D:

Git comparison exposes modified definitions prior to persistence.

Question 286

An engineer needs to create and edit pipelines in a workspace but must not manage membership. Which engineering decision is most suitable for this specific situation?

  1. Maintain the specific item share rather than granting workspace Contributor.
  2. Review supported audit events for role and permission changes.
  3. Assign a managed Microsoft Entra group to the OneLake security role.
  4. Assign the engineer the Contributor workspace role.

Explanation

Correct Answer

D:

Contributor supports creating and modifying workspace content without Member-level sharing management.

Incorrect Answers

A:

Item access is narrower than workspace roles and avoids unnecessary creation and modification rights.

B:

Audit logs provide available governance activity history for investigation.

C:

OneLake security resolves supported Entra group membership for role grants.

Question 287

A business team needs Power Query-style cleansing of a small spreadsheet feed. What should the engineer implement first to satisfy the stated need?

  1. Use summarize max(timestamp) by device_id.
  2. Create a pipeline Copy activity into the destination.
  3. Use Dataflow Gen2 and a configured destination.
  4. Configure the appropriate dataflow schema-drift destination settings.

Explanation

Correct Answer

C:

It provides visual low-code Power Query transformations.

Incorrect Answers

A:

Group-wise max returns each device's latest time.

B:

Copy handles scalable source-to-target data movement.

D:

Dataflow Gen2 offers controlled destination schema updates.

Question 288

Sales analysts share one warehouse table but each analyst should query only rows for the regions assigned to that identity. Which action best addresses the requirement?

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

Explanation

Correct Answer

C:

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

Incorrect Answers

A:

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

B:

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

D:

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

Question 289

In a Microsoft Fabric solution, short notebook jobs always allocate oversized compute resources. Which configuration or implementation should the engineer choose?

  1. Normalize compatible join-key data types.
  2. Move aggregation into distributed Spark expressions.
  3. Use high-concurrency Spark sessions for compatible workloads.
  4. Assign a smaller compatible environment or pool size.

Explanation

Correct Answer

D:

Right-sizing reduces unused capacity while retaining required latency.

Incorrect Answers

A:

Conversions on join paths can increase query cost.

B:

Distributed aggregation avoids huge driver memory use.

C:

Session reuse reduces startup overhead.

Question 290

Spark jobs are short on executor memory for their actual data volume. Which engineering decision is most suitable for this specific situation?

  1. Right-size executor resources in the attached environment.
  2. Use a skew-aware join plan or carefully designed salting.
  3. Use a suitable broadcast join.
  4. Tune shuffle partition count to match volume and resources.

Explanation

Correct Answer

A:

Sufficient compatible executor memory can reduce spills and failures.

Incorrect Answers

B:

Redistribution prevents one worker from becoming a straggler.

C:

Broadcasting small lookup data can avoid shuffling the large fact.

D:

Excess tiny tasks add scheduling overhead.