Databricks Certified Data Engineer Associate Practice Test 62
Question 610
At Community energy cooperative, the catalog schema use privileges workflow handles smart meter readings. The problem is that smart_meter_readings_central analysts have SELECT on a table but get a permission error at query time. Evidence: access review shows missing USE CATALOG on its parent catalog. Constraint: users must read only the authorized governed object. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. What governed target implementation should the engineer design?
- Check current UC parent hierarchy and effective grants for smart_meter_readings_central
- Monitor failed parent-path access and excessive grants for smart_meter_readings_central
- Grant required parent USE CATALOG and USE SCHEMA along with table SELECT
- Grant global metastore administration to fix one table query at Community energy cooperative
Explanation
Correct Answer
C:Grant required parent USE CATALOG and USE SCHEMA along with table SELECT is the intended durable approach for smart_meter_readings_central: it addresses the verified problem (smart_meter_readings_central analysts have SELECT on a table but get a permission error at query time) while preserving the required behavior (users must read only the authorized governed object). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Check current UC parent hierarchy and effective grants for smart_meter_readings_central could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The smart_meter_readings_central workflow still requires that users must read only the authorized governed object.
B:Monitor failed parent-path access and excessive grants for smart_meter_readings_central would help detect future recurrence, but metrics alone do not deliver the target approach. The smart_meter_readings_central requirement is that users must read only the authorized governed object.
D:Global admin rights exceed simple read access needs. The proposed action (Grant global metastore administration to fix one table query at Community energy cooperative) does not meet the requirement that users must read only the authorized governed object, nor does it constitute the target approach.
Question 611
Consider the customer_order_changes_north workload at Online apparel cooperative: customer_order_changes_north contains many tables with a sensitive tag but policy enforcement differs by owner. Inspection found that audit shows only some similarly tagged tables have manual row filters. The governed outcome must ensure that one central rule must apply automatically to matching governed objects. 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?
- Use ungoverned free-text tags and assume they enforce security at Online apparel cooperative
- Define a Unity Catalog ABAC policy using governed tags at an appropriate parent scope
- Inventory governed tag assignments and effective policy scope for customer_order_changes_north
- Monitor tag changes, policy conditions and exemption grants for customer_order_changes_north
Explanation
Correct Answer
B:Define a Unity Catalog ABAC policy using governed tags at an appropriate parent scope is the intended durable approach for customer_order_changes_north: it addresses the verified problem (customer_order_changes_north contains many tables with a sensitive tag but policy enforcement differs by owner) while preserving the required behavior (one central rule must apply automatically to matching governed objects). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Untested labels are not enforced access policies. The proposed action (Use ungoverned free-text tags and assume they enforce security at Online apparel cooperative) does not meet the requirement that one central rule must apply automatically to matching governed objects, nor does it constitute the target approach.
C:Inventory governed tag assignments and effective policy scope for customer_order_changes_north could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The customer_order_changes_north workflow still requires that one central rule must apply automatically to matching governed objects.
D:Monitor tag changes, policy conditions and exemption grants for customer_order_changes_north would help detect future recurrence, but metrics alone do not deliver the target approach. The customer_order_changes_north requirement is that one central rule must apply automatically to matching governed objects.
Question 612
The maintenance_work_orders_metro pipeline at Airport facilities operator has this failure: joining maintenance_work_orders_metro fact records to a tiny reference table produces a large shuffle. The team observed that Spark UI shows both inputs shuffled despite one lookup occupying a few megabytes. Business requirement: join output must retain key equality and correct multiplicity. 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?
- Monitor dimension growth and join-plan regressions for maintenance_work_orders_metro
- Compare join counts and stage shuffle bytes with and without the hint
- Broadcast the eligible small reference DataFrame when appropriate to avoid a large shuffle
- CrossJoin the entire fact and reference datasets then filter after collection at Airport facilities operator
Explanation
Correct Answer
A:Monitor dimension growth and join-plan regressions for maintenance_work_orders_metro creates recurring visibility into the failure mode (joining maintenance_work_orders_metro fact records to a tiny reference table produces a large shuffle). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while join output must retain key equality and correct multiplicity.
Incorrect Answers
B:Compare join counts and stage shuffle bytes with and without the hint is a one-time acceptance check. It does not supply continuing operational detection for maintenance_work_orders_metro; a passing test cannot substitute for the specific task now required.
C:Broadcast the eligible small reference DataFrame when appropriate to avoid a large shuffle is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the maintenance_work_orders_metro scenario, the observed evidence is that Spark UI shows both inputs shuffled despite one lookup occupying a few megabytes; the requirement remains: join output must retain key equality and correct multiplicity.
D:A cartesian expansion wastes resources and risks mis-joins. The proposed action (CrossJoin the entire fact and reference datasets then filter after collection at Airport facilities operator) does not meet the requirement that join output must retain key equality and correct multiplicity, nor does it constitute continuing operational detection.
Question 613
A data engineer at International language school is responsible for class enrollment data. The REST pagination and retries issue is that the class_enrollment_data_delta partner API returns 100 rows per page but the batch stores only the first page. The supporting evidence is that response metadata includes a next cursor that the client ignores. The engineer must ensure that all authorized records must be imported without exceeding API limits. 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?
- Implement cursor pagination with bounded retries and idempotent destination keys
- Monitor page completeness, retries and expired cursors for class_enrollment_data_delta
- Stop after one successful HTTP 200 response at International language school
- Compare source advertised total and destination distinct IDs after a full pull
Explanation
Correct Answer
B:Monitor page completeness, retries and expired cursors for class_enrollment_data_delta creates recurring visibility into the failure mode (the class_enrollment_data_delta partner API returns 100 rows per page but the batch stores only the first page). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while all authorized records must be imported without exceeding API limits.
Incorrect Answers
A:Implement cursor pagination with bounded retries and idempotent destination keys is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the class_enrollment_data_delta scenario, the observed evidence is that response metadata includes a next cursor that the client ignores; the requirement remains: all authorized records must be imported without exceeding API limits.
C:A successful first page does not establish completeness. The proposed action (Stop after one successful HTTP 200 response at International language school) does not meet the requirement that all authorized records must be imported without exceeding API limits, nor does it constitute continuing operational detection.
D:Compare source advertised total and destination distinct IDs after a full pull is a one-time acceptance check. It does not supply continuing operational detection for class_enrollment_data_delta; a passing test cannot substitute for the specific task now required.
Question 614
The vessel_position_events_urban pipeline at Maritime safety agency has this failure: vessel_position_events_urban job points to the dev catalog even after deploying with the production target. The team observed that configuration shows an unresolved dev catalog literal in the bundle. Business requirement: one codebase must deploy safely to different UC environments. 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?
- Inspect bundle variables, target overrides and resolved job config for vessel_position_events_urban
- Replace the Git code with a different unreviewed copy for every environment at Maritime safety agency
- Add tested prod variable overrides and run validation before deploy
- Parameterize environment-specific catalog and resources using Declarative Automation Bundle targets
Explanation
Correct Answer
A:Inspect bundle variables, target overrides and resolved job config for vessel_position_events_urban directly investigates the evidence (configuration shows an unresolved dev catalog literal in the bundle) and distinguishes possible causes of vessel_position_events_urban job points to the dev catalog even after deploying with the production target. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: one codebase must deploy safely to different UC environments.
Incorrect Answers
B:Diverging codebases defeat controlled promotion. The proposed action (Replace the Git code with a different unreviewed copy for every environment at Maritime safety agency) does not meet the requirement that one codebase must deploy safely to different UC environments, nor does it constitute the required pre-change investigation.
C:Add tested prod variable overrides and run validation before deploy 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 configuration shows an unresolved dev catalog literal in the bundle. This matters here because the vessel_position_events_urban pipeline at Maritime safety agency has this failure: vessel_position_events_urban….
D:Parameterize environment-specific catalog and resources using Declarative Automation Bundle targets is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the vessel_position_events_urban scenario, the observed evidence is that configuration shows an unresolved dev catalog literal in the bundle; the requirement remains: one codebase must deploy safely to different UC environments.
Question 615
The monthly_pension_movements_island pipeline at Public pension trustee has this failure: monthly_pension_movements_island quality validation flags an empty input but the pipeline always publishes gold. The team observed that the job DAG lacks an if/else decision based on validation outcome. Business requirement: empty invalid batches must skip publication while still reporting status. 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?
- Deploy a condition and branch tasks using an output from the validator
- Always run publish regardless of validator outcome at Public pension trustee
- Identify the condition output and branch decisions required for monthly_pension_movements_island
- Use a Lakeflow condition task to route pass and fail paths explicitly
Explanation
Correct Answer
C:Identify the condition output and branch decisions required for monthly_pension_movements_island directly investigates the evidence (the job DAG lacks an if/else decision based on validation outcome) and distinguishes possible causes of monthly_pension_movements_island quality validation flags an empty input but the pipeline always publishes gold. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: empty invalid batches must skip publication while still reporting status.
Incorrect Answers
A:Deploy a condition and branch tasks using an output from the validator 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 job DAG lacks an if/else decision based on validation outcome. This matters here because the monthly_pension_movements_island pipeline at Public pension trustee has this failure:….
B:Unconditional publication violates the quality gate. The proposed action (Always run publish regardless of validator outcome at Public pension trustee) does not meet the requirement that empty invalid batches must skip publication while still reporting status, nor does it constitute the required pre-change investigation.
D:Use a Lakeflow condition task to route pass and fail paths explicitly is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the monthly_pension_movements_island scenario, the observed evidence is that the job DAG lacks an if/else decision based on validation outcome; the requirement remains: empty invalid batches must skip publication while still reporting status.
Question 616
A data engineer at Coastal freight alliance is responsible for shipment manifests. The Auto Loader schema evolution issue is that a new optional field appears in shipment_manifests_west JSON files and the ingestion job starts rejecting rows. The supporting evidence is that failure details identify a field absent from the previously inferred schema. The engineer must ensure 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. What evidence establishes that correct output is maintained?
- Pilot the new field, persist the updated schema and restart as required
- Silently drop every unexpected field and label ingestion complete at Coastal freight alliance
- Ingest old and new records and verify preserved fields and captured additions
- Inspect schema inference, evolution mode and rescued data behavior on shipment_manifests_west
Explanation
Correct Answer
C:Ingest old and new records and verify preserved fields and captured additions directly tests the behavior that should change following 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: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. This matters here because a data engineer at Coastal freight alliance is responsible for shipment manifests. The Auto Loader schema evolution….
B:Dropping added fields hides source changes and loses information. The proposed action (Silently drop every unexpected field and label ingestion complete at Coastal freight alliance) 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:Inspect schema inference, evolution mode and rescued data behavior on shipment_manifests_west could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The shipment_manifests_west workflow still requires that new attributes must be captured without silently corrupting existing columns.
Question 617
At Multinational parts distributor, the view versus materialized view workflow handles warehouse movement logs. The problem is that warehouse_movement_logs_west analysts require a simple always-current projection without a stored refresh process. Evidence: a team proposes a materialized view even though the logic is just a lightweight filter. Constraint: data access should reflect up-to-date table rows without unnecessary materialization cost. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. What governed target implementation should the engineer design?
- Use a standard governed view for low-cost logical projection rather than scheduled materialization
- Monitor view permissions, dependency changes and query performance for warehouse_movement_logs_west
- Physically copy the entire source table every time a user opens a dashboard at Multinational parts distributor
- Compare source volatility, query cost and freshness needs for warehouse_movement_logs_west
Explanation
Correct Answer
A:Use a standard governed view for low-cost logical projection rather than scheduled materialization is the intended durable approach for warehouse_movement_logs_west: it addresses the verified problem (warehouse_movement_logs_west analysts require a simple always-current projection without a stored refresh process) while preserving the required behavior (data access should reflect up-to-date table rows without unnecessary materialization cost). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
B:Monitor view permissions, dependency changes and query performance for warehouse_movement_logs_west would help detect future recurrence, but metrics alone do not deliver the target approach. The warehouse_movement_logs_west requirement is that data access should reflect up-to-date table rows without unnecessary materialization cost.
C:Unnecessary full copies increase cost and stale-data risk. The proposed action (Physically copy the entire source table every time a user opens a dashboard at Multinational parts distributor) does not meet the requirement that data access should reflect up-to-date table rows without unnecessary materialization cost, nor does it constitute the target approach.
D:Compare source volatility, query cost and freshness needs for warehouse_movement_logs_west could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The warehouse_movement_logs_west workflow still requires that data access should reflect up-to-date table rows without unnecessary materialization cost.
Question 618
Consider the admission_scan_events_central workload at Regional sporting venue: admission_scan_events_central contains duplicate message IDs after file retries. Inspection found that two rows share event_id but have different ingestion timestamps. The governed outcome must ensure that silver needs one deterministic event per business event identifier. 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?
- Feed repeated IDs in different order and verify the selected canonical record
- Use deterministic row_number or dropDuplicates on the correct business key and ordering rule
- Track duplicate-key rate and conflicting payloads for admission_scan_events_central
- DropDuplicates on every column when duplicates differ only by ingest timestamp at Regional sporting venue
Explanation
Correct Answer
C:Track duplicate-key rate and conflicting payloads for admission_scan_events_central creates recurring visibility into the failure mode (admission_scan_events_central contains duplicate message IDs after file retries). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while silver needs one deterministic event per business event identifier.
Incorrect Answers
A:Feed repeated IDs in different order and verify the selected canonical record is a one-time acceptance check. It does not supply continuing operational detection for admission_scan_events_central; a passing test cannot substitute for the specific task now required.
B: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 continuing operational detection at this stage. In the admission_scan_events_central 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.
D:All-column comparison misses business-key duplicates. The proposed action (DropDuplicates on every column when duplicates differ only by ingest timestamp at Regional sporting venue) does not meet the requirement that silver needs one deterministic event per business event identifier, nor does it constitute continuing operational detection.
Question 619
The land_cover_observations_highland pipeline at Satellite imagery startup has this failure: land_cover_observations_highland validation notebook computes the partition date but downstream tasks use yesterday by default. The team observed that logs show successful validation for one date and export for another. Business requirement: the exported partition must match the validated partition. 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?
- Pass a validated task value to the dependent export task
- Add explicit task-value references and test with nondefault date
- Run an out-of-order input and verify exported partition matches validated date
- Hardcode yesterday in every downstream task at Satellite imagery startup
Explanation
Correct Answer
B:Add explicit task-value references and test with nondefault date provides a bounded way to introduce the approved solution into land_cover_observations_highland and detect an early mismatch. The existing signal is logs show successful validation for one date and export for another; a staged change protects the service requirement (the exported partition must match the validated partition) and makes rollback practical.
Incorrect Answers
A:Pass a validated task value to the dependent export task is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the land_cover_observations_highland scenario, the observed evidence is that logs show successful validation for one date and export for another; the requirement remains: the exported partition must match the validated partition.
C:Run an out-of-order input and verify exported partition matches validated date is a one-time acceptance check. It does not supply the controlled implementation step for land_cover_observations_highland; a passing test cannot substitute for the specific task now required.
D: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 controlled implementation step.
Question 620
At Airport facilities operator, the maintenance work orders workflow depends on maintenance_work_orders_north. Engineers report that maintenance_work_orders_north bronze records include null business IDs that break downstream joins; the evidence is that profiling identifies a small fraction of missing identifiers plus valid optional fields. They require that silver must reject missing required keys but preserve optional null attributes. 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?
- Filter or quarantine null required IDs while applying explicit nullable rules to optional columns
- Call fillna on every field with zero regardless of semantic type at Airport facilities operator
- Verify no null required IDs remain and legitimate optional-null records survive
- Track rejected-row percentage and null-key source patterns in maintenance_work_orders_north
Explanation
Correct Answer
D:Track rejected-row percentage and null-key source patterns in maintenance_work_orders_north creates recurring visibility into the failure mode (maintenance_work_orders_north bronze records include null business IDs that break downstream joins). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while silver must reject missing required keys but preserve optional null attributes.
Incorrect Answers
A:Filter or quarantine null required IDs while applying explicit nullable rules to optional columns is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the maintenance_work_orders_north scenario, the observed evidence is that profiling identifies a small fraction of missing identifiers plus valid optional fields; the requirement remains: silver must reject missing required keys but preserve optional null attributes.
B:Blanket replacement changes data meaning and can corrupt types. The proposed action (Call fillna on every field with zero regardless of semantic type at Airport facilities operator) does not meet the requirement that silver must reject missing required keys but preserve optional null attributes, nor does it constitute continuing operational detection.
C:Verify no null required IDs remain and legitimate optional-null records survive is a one-time acceptance check. It does not supply continuing operational detection for maintenance_work_orders_north; a passing test cannot substitute for the specific task now required.