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Databricks Certified Data Engineer Associate Practice Test 11

Question 100

The sampling_field_notes_north pipeline at Environmental inspection office has this failure: sampling_field_notes_north reporting team plans to drop a UC-managed table but needs its data files retained. The team observed that table ownership review shows storage lifecycle controlled by Unity Catalog. Business requirement: a cleanup must not accidentally delete retained source data. 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. Move to approved external storage only through a supported governed migration
  2. Inspect table type, location and intended retention before dropping sampling_field_notes_north
  3. Drop a disposable test table and verify actual data-lifecycle behavior
  4. Assume managed and external tables always have identical drop semantics at Environmental inspection office

Explanation

Correct Answer

C:

Drop a disposable test table and verify actual data-lifecycle behavior directly tests the behavior that should change after the correction. With the observed evidence (table ownership review shows storage lifecycle controlled by Unity Catalog), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that a cleanup must not accidentally delete retained source data.

Incorrect Answers

A:

Move to approved external storage only through a supported governed migration 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 table ownership review shows storage lifecycle controlled by Unity Catalog.

B:

Inspect table type, location and intended retention before dropping sampling_field_notes_north could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The sampling_field_notes_north workflow still requires that a cleanup must not accidentally delete retained source data.

D:

Uc table type affects ownership and managed data lifecycle. The proposed action (Assume managed and external tables always have identical drop semantics at Environmental inspection office) does not meet the requirement that a cleanup must not accidentally delete retained source data, nor does it constitute the post-change acceptance test.

Question 101

Consider the payment_authorization_records_east workload at E-commerce payments provider: payment_authorization_records_east job fails before any Spark task begins. Inspection found that cluster event log shows an unavailable instance type in the selected region. The governed outcome must ensure that the diagnostic must distinguish compute provisioning failure from ETL code defects. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which continuing signal best reveals recurrence or drift?

  1. Start a fresh cluster then execute one representative task successfully
  2. Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider
  3. Select a supported compute configuration or serverless option that meets the job constraints
  4. Monitor provisioning failures, retries and startup wait time for payment_authorization_records_east

Explanation

Correct Answer

D:

Monitor provisioning failures, retries and startup wait time for payment_authorization_records_east creates recurring visibility into the failure mode (payment_authorization_records_east job fails before any Spark task begins). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the diagnostic must distinguish compute provisioning failure from ETL code defects.

Incorrect Answers

A:

Start a fresh cluster then execute one representative task successfully is a one-time acceptance check. It does not supply continuing operational detection for payment_authorization_records_east; a passing test cannot substitute for the specific task now required.

B:

Query changes cannot fix unavailable compute capacity. The proposed action (Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider) does not meet the requirement that the diagnostic must distinguish compute provisioning failure from ETL code defects, nor does it constitute continuing operational detection.

C:

Select a supported compute configuration or serverless option that meets the job constraints is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the payment_authorization_records_east scenario, the observed evidence is that cluster event log shows an unavailable instance type in the selected region; the requirement remains: the diagnostic must distinguish compute provisioning failure from ETL code defects.

Question 102

At Air quality nonprofit, the pollution measurements workflow depends on pollution_measurements_central. Engineers report that a new optional field appears in pollution_measurements_central JSON files and the ingestion job starts rejecting rows; the evidence is that failure details identify a field absent from the previously inferred schema. They require that new attributes must be captured without silently corrupting existing columns. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. Which post-change acceptance check is strongest?

  1. Inspect schema inference, evolution mode and rescued data behavior on pollution_measurements_central
  2. Ingest old and new records and verify preserved fields and captured additions
  3. Silently drop every unexpected field and label ingestion complete at Air quality nonprofit
  4. Pilot the new field, persist the updated schema and restart as required

Explanation

Correct Answer

B:

Ingest old and new records and verify preserved fields and captured additions directly tests the behavior that should change after the correction. With the observed evidence (failure details identify a field absent from the previously inferred schema), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that new attributes must be captured without silently corrupting existing columns.

Incorrect Answers

A:

Inspect schema inference, evolution mode and rescued data behavior on pollution_measurements_central could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The pollution_measurements_central workflow still requires that new attributes must be captured without silently corrupting existing columns.

C:

Dropping added fields hides source changes and loses information. The proposed action (Silently drop every unexpected field and label ingestion complete at Air quality nonprofit) does not meet the requirement that new attributes must be captured without silently corrupting existing columns, nor does it constitute the post-change acceptance test.

D:

Pilot the new field, persist the updated schema and restart as required 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 failure details identify a field absent from the previously inferred schema.

Question 103

The pollution_measurements_delta pipeline at Air quality nonprofit has this failure: pollution_measurements_delta bundle deployment fails after someone changes its job task reference. The team observed that CLI output identifies invalid resource or variable configuration. Business requirement: the error must be caught before production resources change. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. What lasting solution should be selected for the verified conditions?

  1. Include `databricks bundle validate -t prod` before deployment
  2. Always run bundle deploy despite failing validation at Air quality nonprofit
  3. Inspect bundle manifest, resource paths and reported validator errors for pollution_measurements_delta
  4. Monitor validation failures and unsupported resource configuration in pollution_measurements_delta

Explanation

Correct Answer

A:

Include `databricks bundle validate -t prod` before deployment is the intended durable approach for pollution_measurements_delta: it addresses the verified problem (pollution_measurements_delta bundle deployment fails after someone changes its job task reference) while preserving the required behavior (the error must be caught before production resources change). A diagnostic or monitoring step alone would not create this target-state behavior.

Incorrect Answers

B:

Deploying invalid configuration bypasses the preflight gate. The proposed action (Always run bundle deploy despite failing validation at Air quality nonprofit) does not meet the requirement that the error must be caught before production resources change, nor does it constitute the target approach.

C:

Inspect bundle manifest, resource paths and reported validator errors for pollution_measurements_delta could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The pollution_measurements_delta workflow still requires that the error must be caught before production resources change.

D:

Monitor validation failures and unsupported resource configuration in pollution_measurements_delta would help detect future recurrence, but metrics alone do not deliver the target approach. The pollution_measurements_delta requirement is that the error must be caught before production resources change.

Question 104

Consider the payment_authorization_records_rural workload at E-commerce payments provider: payment_authorization_records_rural ledger export is legally due at 06:00 even when no new records arrive. Inspection found that operators propose a file trigger that may not run on quiet days. The governed outcome must ensure that an empty but valid daily export must still be delivered. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which evidence-gathering action should precede an architectural change?

  1. Deploy cron schedule with a no-new-data success path
  2. Verify whether output requirement is calendar-driven or source-event-driven for payment_authorization_records_rural
  3. Use only file-arrival triggers for a mandatory daily report at E-commerce payments provider
  4. Use a time-based schedule for mandatory daily reporting independent of arrivals

Explanation

Correct Answer

B:

Verify whether output requirement is calendar-driven or source-event-driven for payment_authorization_records_rural directly investigates the evidence (operators propose a file trigger that may not run on quiet days) and distinguishes possible causes of payment_authorization_records_rural ledger export is legally due at 06:00 even when no new records arrive. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: an empty but valid daily export must still be delivered.

Incorrect Answers

A:

Deploy cron schedule with a no-new-data success path 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 operators propose a file trigger that may not run on quiet days.

C:

Quiet source days would skip the required calendar delivery. The proposed action (Use only file-arrival triggers for a mandatory daily report at E-commerce payments provider) does not meet the requirement that an empty but valid daily export must still be delivered, nor does it constitute the required pre-change investigation.

D:

Use a time-based schedule for mandatory daily reporting independent of arrivals is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the payment_authorization_records_rural scenario, the observed evidence is that operators propose a file trigger that may not run on quiet days; the requirement remains: an empty but valid daily export must still be delivered.

Question 105

At Media postproduction team, the render-job telemetry workflow depends on render_job_telemetry_north. Engineers report that render_job_telemetry_north dashboard repeatedly scans years of silver transactions for daily rollups; the evidence is that SQL history shows expensive repeated aggregation on an otherwise stable reporting query. They require that analysts need low-latency aggregates refreshed on a defined cadence. 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. Create a regular view and promise it stores its results between queries at Media postproduction team
  2. Configure a representative refresh schedule and reconcile the initial build
  3. Verify refresh applies new silver rows and queries return the expected totals
  4. Publish a materialized view for precomputed frequently queried aggregates

Explanation

Correct Answer

B:

Configure a representative refresh schedule and reconcile the initial build provides a bounded way to introduce the approved solution into render_job_telemetry_north and detect an early mismatch. The existing signal is SQL history shows expensive repeated aggregation on an otherwise stable reporting query; a staged change protects the service requirement (analysts need low-latency aggregates refreshed on a defined cadence) and makes rollback practical.

Incorrect Answers

A:

Ordinary views do not persist precomputed results. The proposed action (Create a regular view and promise it stores its results between queries at Media postproduction team) does not meet the requirement that analysts need low-latency aggregates refreshed on a defined cadence, nor does it constitute the controlled implementation step.

C:

Verify refresh applies new silver rows and queries return the expected totals is a one-time acceptance check. It does not supply the controlled implementation step for render_job_telemetry_north; a passing test cannot substitute for the specific task now required.

D:

Publish a materialized view for precomputed frequently queried aggregates is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the render_job_telemetry_north scenario, the observed evidence is that SQL history shows expensive repeated aggregation on an otherwise stable reporting query; the requirement remains: analysts need low-latency aggregates refreshed on a defined cadence.

Question 106

A data engineer at Renewable energy operator is responsible for turbine sensor messages. The JDBC watermark extraction issue is that the turbine_sensor_messages_east SQL source is polled hourly but every run extracts its entire ten-year table. The supporting evidence is that source query logs show full scans despite an indexed updated_at column. The engineer must ensure that new and changed rows must load with a replay-safe high-water mark. The first acceptance run passed. The current task is to detect future regressions and changes over time. What repeatable measure detects this failure after go-live?

  1. Monitor watermark gaps, source query cost and late records for turbine_sensor_messages_east
  2. Advance the stored watermark before persisting the extracted batch at Renewable energy operator
  3. Modify an old row and verify incremental fetch plus merge applies its update
  4. Use bounded incremental JDBC reads with a persisted watermark and merge keys

Explanation

Correct Answer

A:

Monitor watermark gaps, source query cost and late records for turbine_sensor_messages_east creates recurring visibility into the failure mode (the turbine_sensor_messages_east SQL source is polled hourly but every run extracts its entire ten-year table). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while new and changed rows must load with a replay-safe high-water mark.

Incorrect Answers

B:

Premature watermark advancement can lose rows on failure. The proposed action (Advance the stored watermark before persisting the extracted batch at Renewable energy operator) does not meet the requirement that new and changed rows must load with a replay-safe high-water mark, nor does it constitute continuing operational detection.

C:

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

D:

Use bounded incremental JDBC reads with a persisted watermark and merge keys is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the turbine_sensor_messages_east 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.

Question 107

At Pet-care booking platform, the Lakeflow run-history regression workflow handles appointment requests. The problem is that appointment_requests_coastal job duration doubles after a code release but task status is green. Evidence: run history shows a persistent trend from 12 to 30 minutes. Constraint: operations must distinguish performance regressions from random short spikes. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which investigation is the strongest first step?

  1. Rely on green status alone and ignore duration changes at Pet-care booking platform
  2. Establish baseline runtime thresholds and stage-level investigation triggers
  3. Compare run-history duration across identical appointment_requests_coastal input sizes and revisions
  4. Add duration alerts and annotate the release time on job history

Explanation

Correct Answer

C:

Compare run-history duration across identical appointment_requests_coastal input sizes and revisions directly investigates the evidence (run history shows a persistent trend from 12 to 30 minutes) and distinguishes possible causes of appointment_requests_coastal job duration doubles after a code release but task status is green. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: operations must distinguish performance regressions from random short spikes.

Incorrect Answers

A:

Successful completion does not imply healthy latency. The proposed action (Rely on green status alone and ignore duration changes at Pet-care booking platform) does not meet the requirement that operations must distinguish performance regressions from random short spikes, nor does it constitute the required pre-change investigation.

B:

Establish baseline runtime thresholds and stage-level investigation triggers is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the appointment_requests_coastal scenario, the observed evidence is that run history shows a persistent trend from 12 to 30 minutes; the requirement remains: operations must distinguish performance regressions from random short spikes.

D:

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 required pre-change investigation, especially given the evidence that run history shows a persistent trend from 12 to 30 minutes.

Question 108

A data engineer at Airport facilities operator is responsible for maintenance work orders. The share cost and egress issue is that maintenance_work_orders_central dataset is shared between clouds and network charges surprise the data provider. The supporting evidence is that billing shows recipient reads create cross-cloud data transfer. The engineer must ensure that sharing must meet cost and policy expectations. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What evidence establishes that correct output is maintained?

  1. Measure recipient location, data volumes and provider/recipient charge terms for maintenance_work_orders_central
  2. Compare actual transfer bytes and charges against the forecast
  3. Assume cross-cloud data transfer is always free because sharing is read-only at Airport facilities operator
  4. Pilot a small cross-cloud share and review billing before expansion

Explanation

Correct Answer

B:

Compare actual transfer bytes and charges against the forecast directly tests the behavior that should change after the correction. With the observed evidence (billing shows recipient reads create cross-cloud data transfer), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that sharing must meet cost and policy expectations.

Incorrect Answers

A:

Measure recipient location, data volumes and provider/recipient charge terms for maintenance_work_orders_central could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The maintenance_work_orders_central workflow still requires that sharing must meet cost and policy expectations.

C:

Read-only sharing can still incur network charges. The proposed action (Assume cross-cloud data transfer is always free because sharing is read-only at Airport facilities operator) does not meet the requirement that sharing must meet cost and policy expectations, nor does it constitute the post-change acceptance test.

D:

Pilot a small cross-cloud share and review billing before expansion 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 billing shows recipient reads create cross-cloud data transfer.

Question 109

A data engineer at Education access provider is responsible for student registration records. The notebook task parameters issue is that student_registration_records_east notebook hardcodes a development catalog and writes there during production runs. The supporting evidence is that job run settings differ from values embedded in the notebook code. The engineer must ensure that the same notebook must respect runtime environment configuration. The first acceptance run passed. The current task is to detect future regressions and changes over time. What repeatable measure detects this failure after go-live?

  1. Edit the source notebook by hand every time the job changes environment at Education access provider
  2. Pass task parameters through supported notebook widgets or job parameters
  3. Monitor unresolved parameters and wrong-environment writes for student_registration_records_east
  4. Run dev and prod parameters and confirm each writes only to its own catalog

Explanation

Correct Answer

C:

Monitor unresolved parameters and wrong-environment writes for student_registration_records_east creates recurring visibility into the failure mode (student_registration_records_east notebook hardcodes a development catalog and writes there during production runs). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the same notebook must respect runtime environment configuration.

Incorrect Answers

A:

Manual code edits are not reproducible parameterization. The proposed action (Edit the source notebook by hand every time the job changes environment at Education access provider) does not meet the requirement that the same notebook must respect runtime environment configuration, nor does it constitute continuing operational detection.

B:

Pass task parameters through supported notebook widgets or job parameters is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the student_registration_records_east scenario, the observed evidence is that job run settings differ from values embedded in the notebook code; the requirement remains: the same notebook must respect runtime environment configuration.

D:

Run dev and prod parameters and confirm each writes only to its own catalog is a one-time acceptance check. It does not supply continuing operational detection for student_registration_records_east; a passing test cannot substitute for the specific task now required.

Question 110

A data engineer at Pet-care booking platform is responsible for appointment requests. The SQL query task issue is that appointment_requests_south team schedules a SQL aggregation by opening a dashboard manually. The supporting evidence is that history shows a query can run on SQL warehouse but has no job task. The engineer must ensure that the query must run automatically before downstream export. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What evidence establishes that correct output is maintained?

  1. Ask analysts to click Run on the query each morning at Pet-care booking platform
  2. Create the scheduled SQL task and bind it to the downstream export
  3. Inspect SQL statement, warehouse privileges and desired task dependencies for appointment_requests_south
  4. Trigger the job and verify SQL query result is available before export

Explanation

Correct Answer

D:

Trigger the job and verify SQL query result is available before export directly tests the behavior that should change after the correction. With the observed evidence (history shows a query can run on SQL warehouse but has no job task), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the query must run automatically before downstream export.

Incorrect Answers

A:

Manual invocation does not provide reliable orchestration. The proposed action (Ask analysts to click Run on the query each morning at Pet-care booking platform) does not meet the requirement that the query must run automatically before downstream export, nor does it constitute the post-change acceptance test.

B:

Create the scheduled SQL task and bind it to the downstream export 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 history shows a query can run on SQL warehouse but has no job task.

C:

Inspect SQL statement, warehouse privileges and desired task dependencies for appointment_requests_south could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The appointment_requests_south workflow still requires that the query must run automatically before downstream export.

Certified Data Engineer Associate Practice Tests