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Databricks Certified Data Engineer Associate Practice Test 1

Question 1

The subscriber_provisioning_logs_north pipeline at Regional telecom operator has this failure: subscriber_provisioning_logs_north production job UI was manually edited after bundle deployment. The team observed that resolved job settings differ from the versioned bundle manifest. Business requirement: releases must remain traceable to approved Git changes. The first acceptance run passed. The current task is to detect future regressions and changes over time. What should be tracked as an operational early warning?

  1. Update the source by copying random current production settings without review at Regional telecom operator
  2. Monitor unexpected UI changes and bundle deployment mismatches for subscriber_provisioning_logs_north
  3. Check resource properties and a smoke run against the approved manifest
  4. Treat the versioned bundle as the source of truth and prohibit unreviewed manual drift

Explanation

Correct Answer

B:

Monitor unexpected UI changes and bundle deployment mismatches for subscriber_provisioning_logs_north creates recurring visibility into the failure mode (subscriber_provisioning_logs_north production job UI was manually edited after bundle deployment). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while releases must remain traceable to approved Git changes.

Incorrect Answers

A:

Unreviewed drift can be promoted into every environment. The proposed action (Update the source by copying random current production settings without review at Regional telecom operator) does not meet the requirement that releases must remain traceable to approved Git changes, nor does it constitute continuing operational detection.

C:

Check resource properties and a smoke run against the approved manifest is a one-time acceptance check. It does not supply continuing operational detection for subscriber_provisioning_logs_north; a passing test cannot substitute for the specific task now required.

D:

Treat the versioned bundle as the source of truth and prohibit unreviewed manual drift is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the subscriber_provisioning_logs_north scenario, the observed evidence is that resolved job settings differ from the versioned bundle manifest; the requirement remains: releases must remain traceable to approved Git changes.

Question 2

At Media postproduction team, the render-job telemetry workflow depends on render_job_telemetry_metro. Engineers report that render_job_telemetry_metro aggregation spends most time scheduling thousands of tiny shuffle tasks; the evidence is that Spark UI shows very low per-task data size and excessive scheduling overhead. They require that performance changes must be benchmarked against the same output. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which pre-change diagnostic will resolve the uncertainty?

  1. Inspect shuffle output size, task duration and partition setting for render_job_telemetry_metro
  2. Tune spark.sql.shuffle.partitions or AQE behavior based on measured shuffle workload
  3. Apply a bounded change in staging and compare resource cost
  4. Increase shuffle partitions without measuring task size or skew at Media postproduction team

Explanation

Correct Answer

A:

Inspect shuffle output size, task duration and partition setting for render_job_telemetry_metro directly investigates the evidence (Spark UI shows very low per-task data size and excessive scheduling overhead) and distinguishes possible causes of render_job_telemetry_metro aggregation spends most time scheduling thousands of tiny shuffle tasks. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: performance changes must be benchmarked against the same output.

Incorrect Answers

B:

Tune spark.sql.shuffle.partitions or AQE behavior based on measured shuffle workload is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the render_job_telemetry_metro scenario, the observed evidence is that Spark UI shows very low per-task data size and excessive scheduling overhead; the requirement remains: performance changes must be benchmarked against the same output.

C:

Apply a bounded change in staging and compare resource cost may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the required pre-change investigation, especially given the evidence that Spark UI shows very low per-task data size and excessive scheduling overhead.

D:

Arbitrary partition expansion can increase overhead. The proposed action (Increase shuffle partitions without measuring task size or skew at Media postproduction team) does not meet the requirement that performance changes must be benchmarked against the same output, nor does it constitute the required pre-change investigation.

Question 3

At Regional telecom operator, the subscriber provisioning logs workflow depends on subscriber_provisioning_logs_north. Engineers report that subscriber_provisioning_logs_north production job UI was manually edited after bundle deployment; the evidence is that resolved job settings differ from the versioned bundle manifest. They require that releases must remain traceable to approved Git changes. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which controlled implementation step is appropriate now?

  1. Update the source by copying random current production settings without review at Regional telecom operator
  2. Treat the versioned bundle as the source of truth and prohibit unreviewed manual drift
  3. Check resource properties and a smoke run against the approved manifest
  4. Reapply the approved bundle after controlled review of production-only changes

Explanation

Correct Answer

D:

Reapply the approved bundle after controlled review of production-only changes provides a bounded way to introduce the approved solution into subscriber_provisioning_logs_north and detect an early mismatch. The existing signal is resolved job settings differ from the versioned bundle manifest; a staged change protects the service requirement (releases must remain traceable to approved Git changes) and makes rollback practical.

Incorrect Answers

A:

Unreviewed drift can be promoted into every environment. The proposed action (Update the source by copying random current production settings without review at Regional telecom operator) does not meet the requirement that releases must remain traceable to approved Git changes, nor does it constitute the controlled implementation step.

B:

Treat the versioned bundle as the source of truth and prohibit unreviewed manual drift is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the subscriber_provisioning_logs_north scenario, the observed evidence is that resolved job settings differ from the versioned bundle manifest; the requirement remains: releases must remain traceable to approved Git changes.

C:

Check resource properties and a smoke run against the approved manifest is a one-time acceptance check. It does not supply the controlled implementation step for subscriber_provisioning_logs_north; a passing test cannot substitute for the specific task now required.

Question 4

At Manufacturing quality network, the factory defect records workflow depends on factory_defect_records_delta. Engineers report that factory_defect_records_delta pipeline configuration exists only in one engineer's workspace UI; the evidence is that releasing to test requires manual reconstruction of tasks. They require that the same versioned workload definitions must deploy to multiple targets. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which platform or PySpark choice best fits the stated semantics?

  1. Inventory job, pipeline and permissions resources needed for factory_defect_records_delta
  2. Package supported jobs and pipelines as Declarative Automation Bundle resources
  3. Monitor resource drift and unmanaged manually edited production jobs for factory_defect_records_delta
  4. Recreate every task manually with different values in each environment at Manufacturing quality network

Explanation

Correct Answer

B:

Package supported jobs and pipelines as Declarative Automation Bundle resources is the intended durable approach for factory_defect_records_delta: it addresses the verified problem (factory_defect_records_delta pipeline configuration exists only in one engineer's workspace UI) while preserving the required behavior (the same versioned workload definitions must deploy to multiple targets). A diagnostic or monitoring step alone would not create this target-state behavior.

Incorrect Answers

A:

Inventory job, pipeline and permissions resources needed for factory_defect_records_delta could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The factory_defect_records_delta workflow still requires that the same versioned workload definitions must deploy to multiple targets.

C:

Monitor resource drift and unmanaged manually edited production jobs for factory_defect_records_delta would help detect future recurrence, but metrics alone do not deliver the target approach. The factory_defect_records_delta requirement is that the same versioned workload definitions must deploy to multiple targets.

D:

Manual recreation invites hidden differences and unreproducible releases. The proposed action (Recreate every task manually with different values in each environment at Manufacturing quality network) does not meet the requirement that the same versioned workload definitions must deploy to multiple targets, nor does it constitute the target approach.

Question 5

Consider the borrower_circulation_events_south workload at City library association: the borrower_circulation_events_south SQL source is polled hourly but every run extracts its entire ten-year table. Inspection found that source query logs show full scans despite an indexed updated_at column. The governed outcome must ensure that new and changed rows must load with a replay-safe high-water mark. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which staged rollout best preserves the existing workload?

  1. Use bounded incremental JDBC reads with a persisted watermark and merge keys
  2. Modify an old row and verify incremental fetch plus merge applies its update
  3. Advance the stored watermark before persisting the extracted batch at City library association
  4. Run an initial backfill, then advance a tested watermark only after successful commit

Explanation

Correct Answer

D:

Run an initial backfill, then advance a tested watermark only after successful commit provides a bounded way to introduce the approved solution into borrower_circulation_events_south and detect an early mismatch. The existing signal is source query logs show full scans despite an indexed updated_at column; a staged change protects the service requirement (new and changed rows must load with a replay-safe high-water mark) and makes rollback practical.

Incorrect Answers

A:

Use bounded incremental JDBC reads with a persisted watermark and merge keys is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the borrower_circulation_events_south scenario, the observed evidence is that source query logs show full scans despite an indexed updated_at column; the requirement remains: new and changed rows must load with a replay-safe high-water mark.

B:

Modify an old row and verify incremental fetch plus merge applies its update is a one-time acceptance check. It does not supply the controlled implementation step for borrower_circulation_events_south; a passing test cannot substitute for the specific task now required.

C:

Premature watermark advancement can lose rows on failure. The proposed action (Advance the stored watermark before persisting the extracted batch at City library association) does not meet the requirement that new and changed rows must load with a replay-safe high-water mark, nor does it constitute the controlled implementation step.

Question 6

The match_session_events_delta pipeline at Cloud gaming cooperative has this failure: match_session_events_delta dataset is shared with a third party that does not run Databricks. The team observed that recipient cannot authenticate to a Databricks workspace but supports the open protocol. Business requirement: the partner needs supported read-only interoperability. The first acceptance run passed. The current task is to detect future regressions and changes over time. What should be tracked as an operational early warning?

  1. Read shared sample data through the external client and validate scope
  2. Choose open Delta Sharing recipient method for eligible non-Databricks consumers
  3. Monitor recipient token expiry and access logs for match_session_events_delta
  4. Require every external organization to obtain provider workspace administrator access at Cloud gaming cooperative

Explanation

Correct Answer

C:

Monitor recipient token expiry and access logs for match_session_events_delta creates recurring visibility into the failure mode (match_session_events_delta dataset is shared with a third party that does not run Databricks). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the partner needs supported read-only interoperability.

Incorrect Answers

A:

Read shared sample data through the external client and validate scope is a one-time acceptance check. It does not supply continuing operational detection for match_session_events_delta; a passing test cannot substitute for the specific task now required.

B:

Choose open Delta Sharing recipient method for eligible non-Databricks consumers is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the match_session_events_delta scenario, the observed evidence is that recipient cannot authenticate to a Databricks workspace but supports the open protocol; the requirement remains: the partner needs supported read-only interoperability.

D:

Workspace administration is not needed for open read-only sharing. The proposed action (Require every external organization to obtain provider workspace administrator access at Cloud gaming cooperative) does not meet the requirement that the partner needs supported read-only interoperability, nor does it constitute continuing operational detection.

Question 7

At Food delivery franchise, the job max concurrent runs workflow handles dispatch and delivery status. The problem is that dispatch_and_delivery_status_highland high-frequency triggers create overlapping job runs that overwrite the same gold partition. Evidence: run history shows two active instances of an identical pipeline. Constraint: concurrent processing must respect destination write semantics. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. Which test should pass before the new flow is accepted?

  1. Pilot concurrency limits and deterministic write keys
  2. Raise maximum concurrent runs without coordinating shared output writes at Food delivery franchise
  3. Inspect overlap, idempotency and safe concurrency limit for dispatch_and_delivery_status_highland
  4. Send overlapping triggers and confirm bounded jobs and consistent output

Explanation

Correct Answer

D:

Send overlapping triggers and confirm bounded jobs and consistent output directly tests the behavior that should change after the correction. With the observed evidence (run history shows two active instances of an identical pipeline), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that concurrent processing must respect destination write semantics.

Incorrect Answers

A:

Pilot concurrency limits and deterministic write keys may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the post-change acceptance test, especially given the evidence that run history shows two active instances of an identical pipeline.

B:

Overlapping unsafe writers can corrupt business results or cause failures. The proposed action (Raise maximum concurrent runs without coordinating shared output writes at Food delivery franchise) does not meet the requirement that concurrent processing must respect destination write semantics, nor does it constitute the post-change acceptance test.

C:

Inspect overlap, idempotency and safe concurrency limit for dispatch_and_delivery_status_highland could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The dispatch_and_delivery_status_highland workflow still requires that concurrent processing must respect destination write semantics.

Question 8

The product_sales_transactions_east pipeline at Online bicycle retailer has this failure: product_sales_transactions_east job duration doubles after a code release but task status is green. The team observed that run history shows a persistent trend from 12 to 30 minutes. Business requirement: operations must distinguish performance regressions from random short spikes. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What test most directly proves the requirement is satisfied?

  1. Add duration alerts and annotate the release time on job history
  2. Rely on green status alone and ignore duration changes at Online bicycle retailer
  3. Reprocess a representative input and compare stage timings to baseline
  4. Compare run-history duration across identical product_sales_transactions_east input sizes and revisions

Explanation

Correct Answer

C:

Reprocess a representative input and compare stage timings to baseline directly tests the behavior that should change after the correction. With the observed evidence (run history shows a persistent trend from 12 to 30 minutes), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that operations must distinguish performance regressions from random short spikes.

Incorrect Answers

A:

Add duration alerts and annotate the release time on job history may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the post-change acceptance test, especially given the evidence that run history shows a persistent trend from 12 to 30 minutes.

B:

Successful completion does not imply healthy latency. The proposed action (Rely on green status alone and ignore duration changes at Online bicycle retailer) does not meet the requirement that operations must distinguish performance regressions from random short spikes, nor does it constitute the post-change acceptance test.

D:

Compare run-history duration across identical product_sales_transactions_east input sizes and revisions could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The product_sales_transactions_east workflow still requires that operations must distinguish performance regressions from random short spikes.

Question 9

At Local government portal, the derived column withColumn workflow handles citizen service applications. The problem is that citizen_service_applications_west needs a normalized discount amount but the pipeline overwrites the source field. Evidence: code review shows an arithmetic expression replacing original gross_sales. Constraint: auditors require gross and net amounts independently. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which monitoring approach will detect newly emerging defects?

  1. Monitor negative net amounts and source-to-derived reconciliation for citizen_service_applications_west
  2. Use withColumn to add a derived net amount while keeping gross_sales unchanged
  3. Overwrite the only gross amount and discard source values at Local government portal
  4. Check discount scenarios and verify both gross and net are correct

Explanation

Correct Answer

A:

Monitor negative net amounts and source-to-derived reconciliation for citizen_service_applications_west creates recurring visibility into the failure mode (citizen_service_applications_west needs a normalized discount amount but the pipeline overwrites the source field). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while auditors require gross and net amounts independently.

Incorrect Answers

B:

Use withColumn to add a derived net amount while keeping gross_sales unchanged is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the citizen_service_applications_west scenario, the observed evidence is that code review shows an arithmetic expression replacing original gross_sales; the requirement remains: auditors require gross and net amounts independently.

C:

Overwriting original financial evidence breaks reconciliation. The proposed action (Overwrite the only gross amount and discard source values at Local government portal) does not meet the requirement that auditors require gross and net amounts independently, nor does it constitute continuing operational detection.

D:

Check discount scenarios and verify both gross and net are correct is a one-time acceptance check. It does not supply continuing operational detection for citizen_service_applications_west; a passing test cannot substitute for the specific task now required.

Question 10

Consider the admission_scan_events_central workload at Regional sporting venue: admission_scan_events_central final export shows success even though an optional upstream data audit failed. Inspection found that the team treats final task status as whole-pipeline correctness. The governed outcome must ensure that operational alerts must reflect required DAG path failures. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which data-engineering approach resolves the documented weakness?

  1. Monitor only the last task while ignoring failed required upstream nodes at Regional sporting venue
  2. Inspect task graph run states and required-versus-optional dependencies for admission_scan_events_central
  3. Set success criteria and notifications on required tasks and aggregate job outcome
  4. Monitor repeated task skips, failure rate and false-green executions for admission_scan_events_central

Explanation

Correct Answer

C:

Set success criteria and notifications on required tasks and aggregate job outcome is the intended durable approach for admission_scan_events_central: it addresses the verified problem (admission_scan_events_central final export shows success even though an optional upstream data audit failed) while preserving the required behavior (operational alerts must reflect required DAG path failures). A diagnostic or monitoring step alone would not create this target-state behavior.

Incorrect Answers

A:

Last-task success does not prove full dag correctness. The proposed action (Monitor only the last task while ignoring failed required upstream nodes at Regional sporting venue) does not meet the requirement that operational alerts must reflect required DAG path failures, nor does it constitute the target approach.

B:

Inspect task graph run states and required-versus-optional dependencies for admission_scan_events_central could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The admission_scan_events_central workflow still requires that operational alerts must reflect required DAG path failures.

D:

Monitor repeated task skips, failure rate and false-green executions for admission_scan_events_central would help detect future recurrence, but metrics alone do not deliver the target approach. The admission_scan_events_central requirement is that operational alerts must reflect required DAG path failures.

Certified Data Engineer Associate Practice Tests