Databricks Certified Data Engineer Associate Practice Test 31
Question 300
At Regional telecom operator, the subscriber provisioning logs workflow depends on subscriber_provisioning_logs_central. Engineers report that subscriber_provisioning_logs_central source timestamps arrive as mixed strings and local offsets; the evidence is that a daily fact report groups the same instant into different dates. They require that event time must use a documented timezone and typed timestamp convention. 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?
- Compare events around midnight and daylight-saving transitions in the output
- Compare time strings lexicographically and ignore offsets at Regional telecom operator
- Inspect sample offsets and source timestamp formats for subscriber_provisioning_logs_central
- Run a pilot cast with invalid values quarantined and documented time policy
Explanation
Correct Answer
A:Compare events around midnight and daylight-saving transitions in the output directly tests the behavior that should change after the correction. With the observed evidence (a daily fact report groups the same instant into different dates), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that event time must use a documented timezone and typed timestamp convention.
Incorrect Answers
B:String ordering and timezone ambiguity are not robust event-time modeling. The proposed action (Compare time strings lexicographically and ignore offsets at Regional telecom operator) does not meet the requirement that event time must use a documented timezone and typed timestamp convention, nor does it constitute the post-change acceptance test.
C:Inspect sample offsets and source timestamp formats for subscriber_provisioning_logs_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 subscriber_provisioning_logs_central workflow still requires that event time must use a documented timezone and typed timestamp convention.
D:Run a pilot cast with invalid values quarantined and documented time policy 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 a daily fact report groups the same instant into different dates.
Question 301
A data engineer at Clinical diagnostics network is responsible for lab sample events. The MERGE key update issue is that lab_sample_events_delta delta target must apply corrected invoice amounts from an incremental feed. The supporting evidence is that the source has two updates for the same invoice_id in one batch. The engineer must ensure that target must have one latest value per invoice after applying ordered changes. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which durable Databricks control best addresses the requirement?
- Monitor ambiguous matches and merge row-change counts for lab_sample_events_delta
- Identify stable merge keys and deduplicate multiple updates in the batch for lab_sample_events_delta
- Use Delta MERGE with a deduplicated source on invoice_id and matched update logic
- MERGE with multiple unfiltered source matches per target key at Clinical diagnostics network
Explanation
Correct Answer
C:Use Delta MERGE with a deduplicated source on invoice_id and matched update logic is the intended durable approach for lab_sample_events_delta: it addresses the verified problem (lab_sample_events_delta delta target must apply corrected invoice amounts from an incremental feed) while preserving the required behavior (target must have one latest value per invoice after applying ordered changes). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Monitor ambiguous matches and merge row-change counts for lab_sample_events_delta would help detect future recurrence, but metrics alone do not deliver the target approach. The lab_sample_events_delta requirement is that target must have one latest value per invoice after applying ordered changes.
B:Identify stable merge keys and deduplicate multiple updates in the batch for lab_sample_events_delta could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The lab_sample_events_delta workflow still requires that target must have one latest value per invoice after applying ordered changes.
D:Ambiguous multiple source matches can make updates nondeterministic or fail. The proposed action (MERGE with multiple unfiltered source matches per target key at Clinical diagnostics network) does not meet the requirement that target must have one latest value per invoice after applying ordered changes, nor does it constitute the target approach.
Question 302
The match_session_events_urban pipeline at Cloud gaming cooperative has this failure: match_session_events_urban test run overwrites production tables because both deployment targets share one catalog. The team observed that resolved bundle targets point to the same UC prefix. Business requirement: development tests must not mutate production data. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. What should be done next to deploy the approved solution?
- Segregate dev/test/prod catalog settings using bundle target overrides
- Deploy a nonproduction copy with unique resource namespace and service identity
- Use identical production destinations and hope developers avoid dangerous input at Cloud gaming cooperative
- Run destructive test inputs and verify production table remains unchanged
Explanation
Correct Answer
B:Deploy a nonproduction copy with unique resource namespace and service identity provides a bounded way to introduce the approved solution into match_session_events_urban and detect an early mismatch. The existing signal is resolved bundle targets point to the same UC prefix; a staged change protects the service requirement (development tests must not mutate production data) and makes rollback practical.
Incorrect Answers
A:Segregate dev/test/prod catalog settings using bundle target overrides is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the match_session_events_urban scenario, the observed evidence is that resolved bundle targets point to the same UC prefix; the requirement remains: development tests must not mutate production data.
C:Shared output targets defeat environment isolation. The proposed action (Use identical production destinations and hope developers avoid dangerous input at Cloud gaming cooperative) does not meet the requirement that development tests must not mutate production data, nor does it constitute the controlled implementation step.
D:Run destructive test inputs and verify production table remains unchanged is a one-time acceptance check. It does not supply the controlled implementation step for match_session_events_urban; a passing test cannot substitute for the specific task now required.
Question 303
At City library association, the borrower circulation events workflow depends on borrower_circulation_events_coastal. Engineers report that mobile borrower_circulation_events_coastal events arrive late and sometimes duplicate within an event-time window; the evidence is that several event IDs reappear after an offline device reconnect. They require that the stream must remove duplicates without retaining infinite state. 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?
- Measure late-arrival distribution and validate event IDs and timestamps for borrower_circulation_events_coastal
- Monitor late-drop counts, state-store size and duplicate output for borrower_circulation_events_coastal
- Retain every key forever in unbounded streaming state at City library association
- Deduplicate with stable event IDs and a bounded event-time watermark
Explanation
Correct Answer
D:Deduplicate with stable event IDs and a bounded event-time watermark is the intended durable approach for borrower_circulation_events_coastal: it addresses the verified problem (mobile borrower_circulation_events_coastal events arrive late and sometimes duplicate within an event-time window) while preserving the required behavior (the stream must remove duplicates without retaining infinite state). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Measure late-arrival distribution and validate event IDs and timestamps for borrower_circulation_events_coastal could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The borrower_circulation_events_coastal workflow still requires that the stream must remove duplicates without retaining infinite state.
B:Monitor late-drop counts, state-store size and duplicate output for borrower_circulation_events_coastal would help detect future recurrence, but metrics alone do not deliver the target approach. The borrower_circulation_events_coastal requirement is that the stream must remove duplicates without retaining infinite state.
C:Unbounded state eventually destabilizes a long-running stream. The proposed action (Retain every key forever in unbounded streaming state at City library association) does not meet the requirement that the stream must remove duplicates without retaining infinite state, nor does it constitute the target approach.
Question 304
A data engineer at Veterinary clinic association is responsible for treatment billing events. The row deduplication keys issue is that treatment_billing_events_west contains duplicate message IDs after file retries. The supporting evidence is that two rows share event_id but have different ingestion timestamps. The engineer must ensure that silver needs one deterministic event per business event identifier. 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?
- DropDuplicates on every column when duplicates differ only by ingest timestamp at Veterinary clinic association
- Pilot a dedup transform while retaining originals in bronze for audit
- Use deterministic row_number or dropDuplicates on the correct business key and ordering rule
- Verify duplicate business keys and ordering fields within treatment_billing_events_west
Explanation
Correct Answer
D:Verify duplicate business keys and ordering fields within treatment_billing_events_west directly investigates the evidence (two rows share event_id but have different ingestion timestamps) and distinguishes possible causes of treatment_billing_events_west contains duplicate message IDs after file retries. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: silver needs one deterministic event per business event identifier.
Incorrect Answers
A:All-column comparison misses business-key duplicates. The proposed action (DropDuplicates on every column when duplicates differ only by ingest timestamp at Veterinary clinic association) does not meet the requirement that silver needs one deterministic event per business event identifier, nor does it constitute the required pre-change investigation.
B:Pilot a dedup transform while retaining originals in bronze for audit 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 two rows share event_id but have different ingestion timestamps. This matters here because a data engineer at Veterinary clinic association is responsible for treatment billing events. The row deduplication….
C:Use deterministic row_number or dropDuplicates on the correct business key and ordering rule is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the treatment_billing_events_west scenario, the observed evidence is that two rows share event_id but have different ingestion timestamps; the requirement remains: silver needs one deterministic event per business event identifier.
Question 305
At Clinical diagnostics network, the lab sample events workflow depends on lab_sample_events_urban. Engineers report that the lab_sample_events_urban import creates a single malformed column because input format settings are wrong; the evidence is that source inspection shows UTF-8 CSV with an explicit header and quoted delimiters. They require that all source columns must map to the intended typed Delta fields. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which ongoing alert or metric is most relevant?
- Choose COPY INTO with the correct CSV fileformat and source column mapping
- Compare parsed field count, null patterns and source record counts
- Load comma-separated records with JSON parsing and suppress all errors at Clinical diagnostics network
- Monitor malformed-file quarantine and schema errors in lab_sample_events_urban
Explanation
Correct Answer
D:Monitor malformed-file quarantine and schema errors in lab_sample_events_urban creates recurring visibility into the failure mode (the lab_sample_events_urban import creates a single malformed column because input format settings are wrong). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while all source columns must map to the intended typed Delta fields.
Incorrect Answers
A:Choose COPY INTO with the correct CSV fileformat and source column mapping is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the lab_sample_events_urban 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.
B:Compare parsed field count, null patterns and source record counts is a one-time acceptance check. It does not supply continuing operational detection for lab_sample_events_urban; a passing test cannot substitute for the specific task now required.
C: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 Clinical diagnostics network) does not meet the requirement that all source columns must map to the intended typed Delta fields, nor does it constitute continuing operational detection.
Question 306
The inventory_adjustments_rural pipeline at Retail pharmacy network has this failure: inventory_adjustments_rural managed table has manual OPTIMIZE jobs colliding with platform-managed maintenance. The team observed that table maintenance history shows overlapping compaction attempts. Business requirement: the maintenance policy must avoid redundant cost and scheduling conflict. 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?
- Manually VACUUM all data files before retention safeguards are checked at Retail pharmacy network
- Use predictive optimization where supported and retire redundant manual jobs
- Disable the overlapping manual maintenance after verifying managed policy
- Inspect table eligibility, predictive optimization configuration and maintenance history for inventory_adjustments_rural
Explanation
Correct Answer
D:Inspect table eligibility, predictive optimization configuration and maintenance history for inventory_adjustments_rural directly investigates the evidence (table maintenance history shows overlapping compaction attempts) and distinguishes possible causes of inventory_adjustments_rural managed table has manual OPTIMIZE jobs colliding with platform-managed maintenance. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: the maintenance policy must avoid redundant cost and scheduling conflict.
Incorrect Answers
A:Unguarded vacuum can remove files needed for recovery. The proposed action (Manually VACUUM all data files before retention safeguards are checked at Retail pharmacy network) does not meet the requirement that the maintenance policy must avoid redundant cost and scheduling conflict, nor does it constitute the required pre-change investigation.
B:Use predictive optimization where supported and retire redundant manual jobs is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the inventory_adjustments_rural scenario, the observed evidence is that table maintenance history shows overlapping compaction attempts; the requirement remains: the maintenance policy must avoid redundant cost and scheduling conflict.
C:Disable the overlapping manual maintenance after verifying managed policy 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 table maintenance history shows overlapping compaction attempts.
Question 307
At Regional hospital network, the clinical appointment reports workflow depends on clinical_appointment_reports_east. Engineers report that clinical_appointment_reports_east job runs hourly although only one file arrives most days; the evidence is that execution history shows repeated empty runs with compute startup cost. They require that process each new delivered file promptly without idle polling. 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?
- Upload a test file and confirm exactly the expected run fires
- Run a full pipeline every minute even if no files arrive at Regional hospital network
- Enable trigger in staging and test a new object arrival
- Inspect file arrival pattern, supported trigger source and job startup overhead for clinical_appointment_reports_east
Explanation
Correct Answer
A:Upload a test file and confirm exactly the expected run fires directly tests the behavior that should change following the correction. With the observed evidence (execution history shows repeated empty runs with compute startup cost), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that process each new delivered file promptly without idle polling.
Incorrect Answers
B:Repetitive empty executions waste compute and cost. The proposed action (Run a full pipeline every minute even if no files arrive at Regional hospital network) does not meet the requirement that process each new delivered file promptly without idle polling, nor does it constitute the post-change acceptance test.
C:Enable trigger in staging and test a new object arrival 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 execution history shows repeated empty runs with compute startup cost. Here, the relevant situation is: the clinical appointment reports workflow depends on clinical_appointment_reports_east. Engineers report that….
D:Inspect file arrival pattern, supported trigger source and job startup overhead for clinical_appointment_reports_east could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The clinical_appointment_reports_east workflow still requires that process each new delivered file promptly without idle polling.
Question 308
The shipment_manifests_west pipeline at Coastal freight alliance has this failure: shipment_manifests_west access exception uses a DENY policy without verifying feature support and scope. The team observed that review finds the target resource is outside the supported ABAC deny-policy securable types. Business requirement: authorization must use supported policy semantics without assuming beta behavior. 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?
- Use supported UC grants and only supported ABAC deny policies where available
- Assume any DENY syntax universally applies to all Unity Catalog objects at Coastal freight alliance
- Pilot the policy in a test catalog and confirm evaluation result
- Verify exact privilege, supported securable type and ABAC DENY feature status for shipment_manifests_west
Explanation
Correct Answer
D:Verify exact privilege, supported securable type and ABAC DENY feature status for shipment_manifests_west directly investigates the evidence (review finds the target resource is outside the supported ABAC deny-policy securable types) and distinguishes possible causes of shipment_manifests_west access exception uses a DENY policy without verifying feature support and scope. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: authorization must use supported policy semantics without assuming beta behavior.
Incorrect Answers
A:Use supported UC grants and only supported ABAC deny policies where available is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the shipment_manifests_west scenario, the observed evidence is that review finds the target resource is outside the supported ABAC deny-policy securable types; the requirement remains: authorization must use supported policy semantics without assuming beta behavior.
B:Beta deny policy semantics are not universal to every securable type. The proposed action (Assume any DENY syntax universally applies to all Unity Catalog objects at Coastal freight alliance) does not meet the requirement that authorization must use supported policy semantics without assuming beta behavior, nor does it constitute the required pre-change investigation.
C:Pilot the policy in a test catalog and confirm evaluation result 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 review finds the target resource is outside the supported ABAC deny-policy securable types.
Question 309
At Multinational parts distributor, the Auto Loader schema evolution workflow handles warehouse movement logs. The problem is that a new optional field appears in warehouse_movement_logs_north JSON files and the ingestion job starts rejecting rows. Evidence: failure details identify a field absent from the previously inferred schema. Constraint: new attributes must be captured without silently corrupting existing columns. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which change can be introduced with minimal production risk?
- Ingest old and new records and verify preserved fields and captured additions
- Silently drop every unexpected field and label ingestion complete at Multinational parts distributor
- Configure supported Auto Loader schema evolution with an explicit schema location and review process
- Pilot the new field, persist the updated schema and restart as required
Explanation
Correct Answer
D:Pilot the new field, persist the updated schema and restart as required provides a bounded way to introduce the approved solution into warehouse_movement_logs_north and detect an early mismatch. The existing signal is failure details identify a field absent from the previously inferred schema; a staged change protects the service requirement (new attributes must be captured without silently corrupting existing columns) and makes rollback practical.
Incorrect Answers
A:Ingest old and new records and verify preserved fields and captured additions is a one-time acceptance check. It does not supply the controlled implementation step for warehouse_movement_logs_north; a passing test cannot substitute for the specific task now required.
B:Dropping added fields hides source changes and loses information. The proposed action (Silently drop every unexpected field and label ingestion complete at Multinational parts distributor) does not meet the requirement that new attributes must be captured without silently corrupting existing columns, nor does it constitute the controlled implementation step.
C:Configure supported Auto Loader schema evolution with an explicit schema location and review process is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the warehouse_movement_logs_north scenario, the observed evidence is that failure details identify a field absent from the previously inferred schema; the requirement remains: new attributes must be captured without silently corrupting existing columns.
Question 310
A data engineer at Manufacturing quality network is responsible for factory defect records. The service principal data grants issue is that factory_defect_records_urban scheduled ingestion succeeds under one employee but fails under automation identity. The supporting evidence is that UC audit shows only the employee has the required table rights. The engineer must ensure that the job must operate under a managed nonhuman least-privilege principal. 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?
- Switch the job identity and verify its input and output access
- Run the pipeline end-to-end using the service principal and deny unrelated catalogs
- Compare job run-as identity and catalog, schema and table grants for factory_defect_records_urban
- Share a workspace administrator's personal access token with all job owners at Manufacturing quality network
Explanation
Correct Answer
B:Run the pipeline end-to-end using the service principal and deny unrelated catalogs directly tests the behavior that should change after the correction. With the observed evidence (UC audit shows only the employee has the required table rights), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the job must operate under a managed nonhuman least-privilege principal.
Incorrect Answers
A:Switch the job identity and verify its input and output access 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 UC audit shows only the employee has the required table rights.
C:Compare job run-as identity and catalog, schema and table grants for factory_defect_records_urban could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The factory_defect_records_urban workflow still requires that the job must operate under a managed nonhuman least-privilege principal.
D:Shared personal tokens are fragile and overprivileged. The proposed action (Share a workspace administrator's personal access token with all job owners at Manufacturing quality network) does not meet the requirement that the job must operate under a managed nonhuman least-privilege principal, nor does it constitute the post-change acceptance test.