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Databricks Certified Data Engineer Associate Practice Test 3

Question 20

At Online bicycle retailer, the library dependency conflict workflow handles product sales transactions. The problem is that product_sales_transactions_island job fails after a Python library upgrade despite unchanged notebook code. Evidence: driver logs show incompatible package versions imported at startup. Constraint: dependency versions must be reproducible across production runs. 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. Compare installed libraries, runtime version and import trace for product_sales_transactions_island
  2. Install random latest packages on shared production compute at Online bicycle retailer
  3. Pin compatible library versions with supported compute/runtime environment
  4. Rebuild a test environment with locked dependencies and execute a smoke run

Explanation

Correct Answer

A:

Compare installed libraries, runtime version and import trace for product_sales_transactions_island directly investigates the evidence (driver logs show incompatible package versions imported at startup) and distinguishes possible causes of product_sales_transactions_island job fails after a Python library upgrade despite unchanged notebook code. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: dependency versions must be reproducible across production runs.

Incorrect Answers

B:

Uncontrolled upgrades can introduce new incompatibilities. The proposed action (Install random latest packages on shared production compute at Online bicycle retailer) does not meet the requirement that dependency versions must be reproducible across production runs, nor does it constitute the required pre-change investigation.

C:

Pin compatible library versions with supported compute/runtime environment is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the product_sales_transactions_island scenario, the observed evidence is that driver logs show incompatible package versions imported at startup; the requirement remains: dependency versions must be reproducible across production runs.

D:

Rebuild a test environment with locked dependencies and execute a smoke run 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 driver logs show incompatible package versions imported at startup.

Question 21

At Port customs authority, the batch versus streaming SLA workflow handles border inspection results. The problem is that the border_inspection_results_rural telemetry producer emits events every few seconds but dashboards only need daily totals. Evidence: profiling shows expensive continuous compute for an overnight business report. Constraint: ingestion frequency should reflect true freshness requirements and cost. 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 SLA misses and idle compute cost for border_inspection_results_rural
  2. Force continuous high-cost processing solely because the source emits events frequently at Port customs authority
  3. Choose scheduled incremental batch when a daily SLA does not warrant continuous processing
  4. Verify next-morning output and source-to-target reconciliation

Explanation

Correct Answer

A:

Monitor SLA misses and idle compute cost for border_inspection_results_rural creates recurring visibility into the failure mode (the border_inspection_results_rural telemetry producer emits events every few seconds but dashboards only need daily totals). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while ingestion frequency should reflect true freshness requirements and cost.

Incorrect Answers

B:

Source frequency alone does not justify a continuous target pipeline. The proposed action (Force continuous high-cost processing solely because the source emits events frequently at Port customs authority) does not meet the requirement that ingestion frequency should reflect true freshness requirements and cost, nor does it constitute continuing operational detection.

C:

Choose scheduled incremental batch when a daily SLA does not warrant continuous processing is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the border_inspection_results_rural scenario, the observed evidence is that profiling shows expensive continuous compute for an overnight business report; the requirement remains: ingestion frequency should reflect true freshness requirements and cost.

D:

Verify next-morning output and source-to-target reconciliation is a one-time acceptance check. It does not supply continuing operational detection for border_inspection_results_rural; a passing test cannot substitute for the specific task now required.

Question 22

Consider the admission_scan_events_west workload at Regional sporting venue: admission_scan_events_west automation configuration contains an API password committed to Git. Inspection found that repository scan detects a plaintext production secret in bundle variables. The governed outcome must ensure that configuration must remain reproducible without exposing secrets. 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. Hide the password by renaming its variable key at Regional sporting venue
  2. Identify secret locations, references and exposed Git history for admission_scan_events_west
  3. Reference approved secret storage or injected CI variables rather than plaintext passwords
  4. Revoke exposed credentials and replace config with secure references

Explanation

Correct Answer

B:

Identify secret locations, references and exposed Git history for admission_scan_events_west directly investigates the evidence (repository scan detects a plaintext production secret in bundle variables) and distinguishes possible causes of admission_scan_events_west automation configuration contains an API password committed to Git. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: configuration must remain reproducible without exposing secrets.

Incorrect Answers

A:

Renaming a plaintext secret does not protect it. The proposed action (Hide the password by renaming its variable key at Regional sporting venue) does not meet the requirement that configuration must remain reproducible without exposing secrets, nor does it constitute the required pre-change investigation.

C:

Reference approved secret storage or injected CI variables rather than plaintext passwords is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the admission_scan_events_west scenario, the observed evidence is that repository scan detects a plaintext production secret in bundle variables; the requirement remains: configuration must remain reproducible without exposing secrets.

D:

Revoke exposed credentials and replace config with secure references 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 repository scan detects a plaintext production secret in bundle variables.

Question 23

A data engineer at Municipal waste service is responsible for collection telemetry. The dashboard task ordering issue is that collection_telemetry_highland executive dashboard refreshes before its gold dataset is updated. The supporting evidence is that job run graph has no edge from aggregation to dashboard refresh. The engineer must ensure that dashboards must represent the latest committed daily snapshot. 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. Refresh the dashboard before materializing the gold data at Municipal waste service
  2. Use a Lakeflow dashboard task dependent on successful upstream gold refresh
  3. Change source data and verify dashboard refresh occurs after processing
  4. Monitor stale dashboard refreshes and upstream task failures for collection_telemetry_highland

Explanation

Correct Answer

D:

Monitor stale dashboard refreshes and upstream task failures for collection_telemetry_highland creates recurring visibility into the failure mode (collection_telemetry_highland executive dashboard refreshes before its gold dataset is updated). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while dashboards must represent the latest committed daily snapshot.

Incorrect Answers

A:

The dashboard would show stale results. The proposed action (Refresh the dashboard before materializing the gold data at Municipal waste service) does not meet the requirement that dashboards must represent the latest committed daily snapshot, nor does it constitute continuing operational detection.

B:

Use a Lakeflow dashboard task dependent on successful upstream gold refresh is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the collection_telemetry_highland scenario, the observed evidence is that job run graph has no edge from aggregation to dashboard refresh; the requirement remains: dashboards must represent the latest committed daily snapshot.

C:

Change source data and verify dashboard refresh occurs after processing is a one-time acceptance check. It does not supply continuing operational detection for collection_telemetry_highland; a passing test cannot substitute for the specific task now required.

Question 24

At Local government portal, the citizen service applications workflow depends on citizen_service_applications_metro. Engineers report that citizen_service_applications_metro orders disappear from silver after a dimension join; the evidence is that audit shows some orders have a missing matching customer row. They require that all fact orders must remain visible even if a dimension lookup fails. 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. Use a left join from facts to customer dimension and flag unmatched rows
  2. Introduce the corrected join with data-quality quarantine for missing attributes
  3. Replace the fact join with inner join and discard nonmatches at Local government portal
  4. Count unmatched keys and examine join predicates for citizen_service_applications_metro

Explanation

Correct Answer

D:

Count unmatched keys and examine join predicates for citizen_service_applications_metro directly investigates the evidence (audit shows some orders have a missing matching customer row) and distinguishes possible causes of citizen_service_applications_metro orders disappear from silver after a dimension join. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: all fact orders must remain visible even if a dimension lookup fails.

Incorrect Answers

A:

Use a left join from facts to customer dimension and flag unmatched rows is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the citizen_service_applications_metro scenario, the observed evidence is that audit shows some orders have a missing matching customer row; the requirement remains: all fact orders must remain visible even if a dimension lookup fails.

B:

Introduce the corrected join with data-quality quarantine for missing attributes 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 audit shows some orders have a missing matching customer row.

C:

An inner join suppresses facts when the right-side lookup is absent. The proposed action (Replace the fact join with inner join and discard nonmatches at Local government portal) does not meet the requirement that all fact orders must remain visible even if a dimension lookup fails, nor does it constitute the required pre-change investigation.

Question 25

Consider the turbine_sensor_messages_coastal workload at Renewable energy operator: turbine_sensor_messages_coastal job succeeds for a developer but fails under the production scheduler. Inspection found that audit logs show a personal identity has access that the service principal lacks. The governed outcome must ensure that production execution must use a durable least-privilege identity. 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. Monitor permission failures and role creep for turbine_sensor_messages_coastal
  2. Execute a full run using the service principal and verify output
  3. Share the developer's personal access token as a permanent production secret at Renewable energy operator
  4. Configure a scoped service principal job identity with required UC privileges

Explanation

Correct Answer

A:

Monitor permission failures and role creep for turbine_sensor_messages_coastal creates recurring visibility into the failure mode (turbine_sensor_messages_coastal job succeeds for a developer but fails under the production scheduler). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while production execution must use a durable least-privilege identity.

Incorrect Answers

B:

Execute a full run using the service principal and verify output is a one-time acceptance check. It does not supply continuing operational detection for turbine_sensor_messages_coastal; a passing test cannot substitute for the specific task now required.

C:

Personal tokens are not durable least-privilege job identities. The proposed action (Share the developer's personal access token as a permanent production secret at Renewable energy operator) does not meet the requirement that production execution must use a durable least-privilege identity, nor does it constitute continuing operational detection.

D:

Configure a scoped service principal job identity with required UC privileges is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the turbine_sensor_messages_coastal scenario, the observed evidence is that audit logs show a personal identity has access that the service principal lacks; the requirement remains: production execution must use a durable least-privilege identity.

Question 26

A data engineer at Multinational parts distributor is responsible for warehouse movement logs. The bundle CLI validation issue is that warehouse_movement_logs_metro bundle deployment fails after someone changes its job task reference. The supporting evidence is that CLI output identifies invalid resource or variable configuration. The engineer must ensure that the error must be caught before production resources change. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. What analysis is necessary before deciding on remediation?

  1. Include `databricks bundle validate -t prod` before deployment
  2. Always run bundle deploy despite failing validation at Multinational parts distributor
  3. Inspect bundle manifest, resource paths and reported validator errors for warehouse_movement_logs_metro
  4. Add validation to CI and fail the job on errors

Explanation

Correct Answer

C:

Inspect bundle manifest, resource paths and reported validator errors for warehouse_movement_logs_metro directly investigates the evidence (CLI output identifies invalid resource or variable configuration) and distinguishes possible causes of warehouse_movement_logs_metro bundle deployment fails after someone changes its job task reference. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: the error must be caught before production resources change.

Incorrect Answers

A:

Include `databricks bundle validate -t prod` before deployment is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the warehouse_movement_logs_metro scenario, the observed evidence is that CLI output identifies invalid resource or variable configuration; the requirement remains: the error must be caught before production resources change.

B:

Deploying invalid configuration bypasses the preflight gate. The proposed action (Always run bundle deploy despite failing validation at Multinational parts distributor) does not meet the requirement that the error must be caught before production resources change, nor does it constitute the required pre-change investigation.

D:

Add validation to CI and fail the job on errors 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 CLI output identifies invalid resource or variable configuration.

Question 27

At Multi-region rental platform, the property reservation updates workflow depends on property_reservation_updates_highland. Engineers report that a streaming file reader for property_reservation_updates_highland reprocesses historical data after every job restart; the evidence is that the streaming query creates a new checkpoint directory on each run. They require that a restart must resume discovered files instead of replaying all existing input. 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. Deploy the stream with a durable checkpoint and restart the same logical query
  2. Delete checkpoint state as part of each successful load at Multi-region rental platform
  3. Inspect checkpoint continuity, discovery progress and input file identifiers
  4. Configure cloudFiles with a stable checkpoint path for the property_reservation_updates_highland stream

Explanation

Correct Answer

C:

Inspect checkpoint continuity, discovery progress and input file identifiers directly investigates the evidence (the streaming query creates a new checkpoint directory on each run) and distinguishes possible causes of a streaming file reader for property_reservation_updates_highland reprocesses historical data after every job restart. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: a restart must resume discovered files instead of replaying all existing input.

Incorrect Answers

A:

Deploy the stream with a durable checkpoint and restart the same logical query 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 the streaming query creates a new checkpoint directory on each run.

B:

Deleting checkpoint progress can cause full replay. The proposed action (Delete checkpoint state as part of each successful load at Multi-region rental platform) does not meet the requirement that a restart must resume discovered files instead of replaying all existing input, nor does it constitute the required pre-change investigation.

D:

Configure cloudFiles with a stable checkpoint path for the property_reservation_updates_highland stream is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the property_reservation_updates_highland scenario, the observed evidence is that the streaming query creates a new checkpoint directory on each run; the requirement remains: a restart must resume discovered files instead of replaying all existing input.

Question 28

The trade_settlement_files_delta pipeline at Wholesale produce exchange has this failure: the trade_settlement_files_delta import creates a single malformed column because input format settings are wrong. The team observed that source inspection shows UTF-8 CSV with an explicit header and quoted delimiters. Business requirement: all source columns must map to the intended typed Delta fields. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. What should the engineer inspect to establish the failure mechanism?

  1. Load comma-separated records with JSON parsing and suppress all errors at Wholesale produce exchange
  2. Inspect sample files and COPY INTO format options for trade_settlement_files_delta
  3. Choose COPY INTO with the correct CSV fileformat and source column mapping
  4. Test the file format on a small sample, then run the governed target load

Explanation

Correct Answer

B:

Inspect sample files and COPY INTO format options for trade_settlement_files_delta directly investigates the evidence (source inspection shows UTF-8 CSV with an explicit header and quoted delimiters) and distinguishes possible causes of the trade_settlement_files_delta import creates a single malformed column because input format settings are wrong. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: all source columns must map to the intended typed Delta fields.

Incorrect Answers

A:

The parser would misread the source schema rather than fix its mapping. The proposed action (Load comma-separated records with JSON parsing and suppress all errors at Wholesale produce exchange) does not meet the requirement that all source columns must map to the intended typed Delta fields, nor does it constitute the required pre-change investigation.

C:

Choose COPY INTO with the correct CSV fileformat and source column mapping is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the trade_settlement_files_delta scenario, the observed evidence is that source inspection shows UTF-8 CSV with an explicit header and quoted delimiters; the requirement remains: all source columns must map to the intended typed Delta fields.

D:

Test the file format on a small sample, then run the governed target load 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 source inspection shows UTF-8 CSV with an explicit header and quoted delimiters.

Question 29

A data engineer at Coastal freight alliance is responsible for shipment manifests. The Lakehouse Federation source issue is that shipment_manifests_north analysts need occasional queries of an external warehouse without full bulk ingestion. The supporting evidence is that source data is large but analytics needs a small live subset. The engineer must ensure that governance should provide on-demand read access without an unnecessary copy. 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 federated query latency and external connection failures for shipment_manifests_north
  2. Query the external source through UC and compare returned authorized rows
  3. Use Lakehouse Federation connection and foreign catalog for suitable source queries
  4. Copy the entire external database daily regardless of query demand at Coastal freight alliance

Explanation

Correct Answer

A:

Monitor federated query latency and external connection failures for shipment_manifests_north creates recurring visibility into the failure mode (shipment_manifests_north analysts need occasional queries of an external warehouse without full bulk ingestion). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while governance should provide on-demand read access without an unnecessary copy.

Incorrect Answers

B:

Query the external source through UC and compare returned authorized rows is a one-time acceptance check. It does not supply continuing operational detection for shipment_manifests_north; a passing test cannot substitute for the specific task now required.

C:

Use Lakehouse Federation connection and foreign catalog for suitable source queries is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the shipment_manifests_north scenario, the observed evidence is that source data is large but analytics needs a small live subset; the requirement remains: governance should provide on-demand read access without an unnecessary copy.

D:

Full-copy ingestion is not required for selective federated querying. The proposed action (Copy the entire external database daily regardless of query demand at Coastal freight alliance) does not meet the requirement that governance should provide on-demand read access without an unnecessary copy, nor does it constitute continuing operational detection.

Question 30

A data engineer at Satellite imagery startup is responsible for land-cover observations. The task value passing issue is that land_cover_observations_highland validation notebook computes the partition date but downstream tasks use yesterday by default. The supporting evidence is that logs show successful validation for one date and export for another. The engineer must ensure that the exported partition must match the validated partition. 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. Add explicit task-value references and test with nondefault date
  2. Hardcode yesterday in every downstream task at Satellite imagery startup
  3. Run an out-of-order input and verify exported partition matches validated date
  4. Inspect taskValues producer, dependency and dynamic reference in land_cover_observations_highland

Explanation

Correct Answer

C:

Run an out-of-order input and verify exported partition matches validated date directly tests the behavior that should change after the correction. With the observed evidence (logs show successful validation for one date and export for another), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the exported partition must match the validated partition.

Incorrect Answers

A:

Add explicit task-value references and test with nondefault date 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 logs show successful validation for one date and export for another.

B:

Hardcoded dates can diverge from validated data. The proposed action (Hardcode yesterday in every downstream task at Satellite imagery startup) does not meet the requirement that the exported partition must match the validated partition, nor does it constitute the post-change acceptance test.

D:

Inspect taskValues producer, dependency and dynamic reference in land_cover_observations_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 land_cover_observations_highland workflow still requires that the exported partition must match the validated partition.

Certified Data Engineer Associate Practice Tests