Databricks Certified Data Engineer Associate Practice Test 96
Question 950
At E-commerce payments provider, the payment authorization records workflow depends on payment_authorization_records_rural. Engineers report that payment_authorization_records_rural ledger export is legally due at 06:00 even when no new records arrive; the evidence is that operators propose a file trigger that may not run on quiet days. They require that an empty but valid daily export must still be delivered. 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?
- Use only file-arrival triggers for a mandatory daily report at E-commerce payments provider
- Monitor deadline misses and incomplete empty-day acknowledgments for payment_authorization_records_rural
- Use a time-based schedule for mandatory daily reporting independent of arrivals
- Verify whether output requirement is calendar-driven or source-event-driven for payment_authorization_records_rural
Explanation
Correct Answer
C:Use a time-based schedule for mandatory daily reporting independent of arrivals is the intended durable approach for payment_authorization_records_rural: it addresses the verified problem (payment_authorization_records_rural ledger export is legally due at 06:00 even when no new records arrive) while preserving the required behavior (an empty but valid daily export must still be delivered). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A: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 target approach.
B:Monitor deadline misses and incomplete empty-day acknowledgments for payment_authorization_records_rural would help detect future recurrence, but metrics alone do not deliver the target approach. The payment_authorization_records_rural requirement is that an empty but valid daily export must still be delivered.
D:Verify whether output requirement is calendar-driven or source-event-driven for payment_authorization_records_rural could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The payment_authorization_records_rural workflow still requires that an empty but valid daily export must still be delivered.
Question 951
At Multinational parts distributor, the warehouse movement logs workflow depends on warehouse_movement_logs_west. Engineers report that warehouse_movement_logs_west former intern still reads a sensitive table after leaving the team; the evidence is that UC audit shows the intern belongs to a group with lingering SELECT privilege. They require that departed identities must lose data access promptly. 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?
- Rename the sensitive table instead of revoking access at Multinational parts distributor
- Remove inappropriate group privileges or membership while keeping service access
- Monitor stale memberships and unauthorized access attempts to warehouse_movement_logs_west
- Trace effective access through group memberships and inherited grants for warehouse_movement_logs_west
Explanation
Correct Answer
B:Remove inappropriate group privileges or membership while keeping service access is the intended durable approach for warehouse_movement_logs_west: it addresses the verified problem (warehouse_movement_logs_west former intern still reads a sensitive table after leaving the team) while preserving the required behavior (departed identities must lose data access promptly). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Renaming an object is not an access-control boundary. The proposed action (Rename the sensitive table instead of revoking access at Multinational parts distributor) does not meet the requirement that departed identities must lose data access promptly, nor does it constitute the target approach.
C:Monitor stale memberships and unauthorized access attempts to 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 departed identities must lose data access promptly.
D:Trace effective access through group memberships and inherited grants 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 departed identities must lose data access promptly.
Question 952
Consider the warehouse_movement_logs_west workload at Multinational parts distributor: warehouse_movement_logs_west former intern still reads a sensitive table after leaving the team. Inspection found that UC audit shows the intern belongs to a group with lingering SELECT privilege. The governed outcome must ensure that departed identities must lose data access promptly. 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?
- Trace effective access through group memberships and inherited grants for warehouse_movement_logs_west
- Rename the sensitive table instead of revoking access at Multinational parts distributor
- Remove inappropriate group privileges or membership while keeping service access
- Revoke access in controlled scope and test authorized user continuity
Explanation
Correct Answer
A:Trace effective access through group memberships and inherited grants for warehouse_movement_logs_west directly investigates the evidence (UC audit shows the intern belongs to a group with lingering SELECT privilege) and distinguishes possible causes of warehouse_movement_logs_west former intern still reads a sensitive table after leaving the team. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: departed identities must lose data access promptly.
Incorrect Answers
B:Renaming an object is not an access-control boundary. The proposed action (Rename the sensitive table instead of revoking access at Multinational parts distributor) does not meet the requirement that departed identities must lose data access promptly, nor does it constitute the required pre-change investigation.
C:Remove inappropriate group privileges or membership while keeping service access 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_west scenario, the observed evidence is that UC audit shows the intern belongs to a group with lingering SELECT privilege; the requirement remains: departed identities must lose data access promptly.
D:Revoke access in controlled scope and test authorized user continuity 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 UC audit shows the intern belongs to a group with lingering SELECT privilege. This matters here because consider the warehouse_movement_logs_west workload at Multinational parts distributor: warehouse_movement_logs_west….
Question 953
Consider the subscriber_provisioning_logs_metro workload at Regional telecom operator: subscriber_provisioning_logs_metro Gold dashboard shows wrong revenue and owners cannot trace the upstream dataset. Inspection found that lineage view is missing a newly added silver transformation. The governed outcome must ensure that impact analysis needs upstream and downstream dependency visibility. 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?
- Instrument or update the supported job dependency record before release
- Use Unity Catalog lineage and supported pipeline metadata to trace data dependencies
- Rely on file naming conventions as proof of full lineage at Regional telecom operator
- Inspect lineage graph and actual query/job references for subscriber_provisioning_logs_metro
Explanation
Correct Answer
D:Inspect lineage graph and actual query/job references for subscriber_provisioning_logs_metro directly investigates the evidence (lineage view is missing a newly added silver transformation) and distinguishes possible causes of subscriber_provisioning_logs_metro Gold dashboard shows wrong revenue and owners cannot trace the upstream dataset. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: impact analysis needs upstream and downstream dependency visibility.
Incorrect Answers
A:Instrument or update the supported job dependency record before release 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 lineage view is missing a newly added silver transformation. This matters here because consider the subscriber_provisioning_logs_metro workload at Regional telecom operator:….
B:Use Unity Catalog lineage and supported pipeline metadata to trace data dependencies is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the subscriber_provisioning_logs_metro scenario, the observed evidence is that lineage view is missing a newly added silver transformation; the requirement remains: impact analysis needs upstream and downstream dependency visibility.
C:Names alone cannot prove transformations and dependencies. The proposed action (Rely on file naming conventions as proof of full lineage at Regional telecom operator) does not meet the requirement that impact analysis needs upstream and downstream dependency visibility, nor does it constitute the required pre-change investigation.
Question 954
At Renewable energy operator, the turbine sensor messages workflow depends on turbine_sensor_messages_south. Engineers report that turbine_sensor_messages_south downstream transformation needs to run after its governed source table changes; the evidence is that the source updates irregularly while cron polling starts empty jobs. They require that data freshness should follow actual table changes rather than wall-clock guesses. 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?
- Modify source and confirm downstream task runs only after detectable update
- Enable the data-driven trigger and run a controlled upstream update
- Configure a table-update trigger tied to the supported source table
- Schedule a blind daily task when source updates require immediate processing at Renewable energy operator
Explanation
Correct Answer
B:Enable the data-driven trigger and run a controlled upstream update provides a bounded way to introduce the approved solution into turbine_sensor_messages_south and detect an early mismatch. The existing signal is the source updates irregularly while cron polling starts empty jobs; a staged change protects the service requirement (data freshness should follow actual table changes rather than wall-clock guesses) and makes rollback practical.
Incorrect Answers
A:Modify source and confirm downstream task runs only after detectable update is a one-time acceptance check. It does not supply the controlled implementation step for turbine_sensor_messages_south; a passing test cannot substitute for the specific task now required.
C:Configure a table-update trigger tied to the supported source table is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the turbine_sensor_messages_south scenario, the observed evidence is that the source updates irregularly while cron polling starts empty jobs; the requirement remains: data freshness should follow actual table changes rather than wall-clock guesses.
D:Coarse polling cannot consistently meet data-driven freshness. The proposed action (Schedule a blind daily task when source updates require immediate processing at Renewable energy operator) does not meet the requirement that data freshness should follow actual table changes rather than wall-clock guesses, nor does it constitute the controlled implementation step.
Question 955
The smart_meter_readings_delta pipeline at Community energy cooperative has this failure: smart_meter_readings_delta table exposes national IDs to analysts who need only transaction amounts. The team observed that query review shows raw identifier values in common reports. Business requirement: users without an approved role must see masked sensitive columns. 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?
- Rename identifier column to a harmless label while leaving values visible at Community energy cooperative
- Apply Unity Catalog column masks or suitable centrally governed masking policy
- Identify sensitive attributes, entitled roles and current query exposure for smart_meter_readings_delta
- Attach the mask in staging with explicit tested identity rules
Explanation
Correct Answer
C:Identify sensitive attributes, entitled roles and current query exposure for smart_meter_readings_delta directly investigates the evidence (query review shows raw identifier values in common reports) and distinguishes possible causes of smart_meter_readings_delta table exposes national IDs to analysts who need only transaction amounts. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: users without an approved role must see masked sensitive columns.
Incorrect Answers
A:Renaming a column does not protect its contents. The proposed action (Rename identifier column to a harmless label while leaving values visible at Community energy cooperative) does not meet the requirement that users without an approved role must see masked sensitive columns, nor does it constitute the required pre-change investigation.
B:Apply Unity Catalog column masks or suitable centrally governed masking policy is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the smart_meter_readings_delta scenario, the observed evidence is that query review shows raw identifier values in common reports; the requirement remains: users without an approved role must see masked sensitive columns.
D:Attach the mask in staging with explicit tested identity rules 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 query review shows raw identifier values in common reports. This matters here because the smart_meter_readings_delta pipeline at Community energy cooperative has this failure: smart_meter_readings_delta….
Question 956
At Aquaculture farming group, the Auto Loader notification discovery workflow handles water-quality readings. The problem is that the water_quality_readings_rural landing zone has millions of objects and directory discovery is becoming expensive. Evidence: ingestion latency rises as source listing grows while only a few files arrive. Constraint: incremental detection must scale without repeatedly listing the whole prefix. 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?
- Enable managed file-event discovery on a pilot source and retain checkpoint state
- Select supported managed file events or notification mode when appropriate
- Measure file discovery delay and completeness as the prefix grows
- Recursively list the entire object-store prefix every second at Aquaculture farming group
Explanation
Correct Answer
A:Enable managed file-event discovery on a pilot source and retain checkpoint state provides a bounded way to introduce the approved solution into water_quality_readings_rural and detect an early mismatch. The existing signal is ingestion latency rises as source listing grows while only a few files arrive; a staged change protects the service requirement (incremental detection must scale without repeatedly listing the whole prefix) and makes rollback practical.
Incorrect Answers
B:Select supported managed file events or notification mode when appropriate is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the water_quality_readings_rural scenario, the observed evidence is that ingestion latency rises as source listing grows while only a few files arrive; the requirement remains: incremental detection must scale without repeatedly listing the whole prefix.
C:Measure file discovery delay and completeness as the prefix grows is a one-time acceptance check. It does not supply the controlled implementation step for water_quality_readings_rural; a passing test cannot substitute for the specific task now required.
D:Repeated full listings increase costs and discovery latency. The proposed action (Recursively list the entire object-store prefix every second at Aquaculture farming group) does not meet the requirement that incremental detection must scale without repeatedly listing the whole prefix, nor does it constitute the controlled implementation step.
Question 957
A data engineer at Air quality nonprofit is responsible for pollution measurements. The Auto Loader schema evolution issue is that a new optional field appears in pollution_measurements_central 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 failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which durable Databricks control best addresses the requirement?
- Inspect schema inference, evolution mode and rescued data behavior on pollution_measurements_central
- Silently drop every unexpected field and label ingestion complete at Air quality nonprofit
- Monitor schema changes, rescued columns and parsing failures for pollution_measurements_central
- Configure supported Auto Loader schema evolution with an explicit schema location and review process
Explanation
Correct Answer
D:Configure supported Auto Loader schema evolution with an explicit schema location and review process is the intended durable approach for pollution_measurements_central: it addresses the verified problem (a new optional field appears in pollution_measurements_central JSON files and the ingestion job starts rejecting rows) while preserving the required behavior (new attributes must be captured without silently corrupting existing columns). A diagnostic or monitoring step alone would not create this target-state behavior.
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 target approach now requested. The pollution_measurements_central workflow still requires that new attributes must be captured without silently corrupting existing columns.
B: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 target approach.
C:Monitor schema changes, rescued columns and parsing failures for pollution_measurements_central would help detect future recurrence, but metrics alone do not deliver the target approach. The pollution_measurements_central requirement is that new attributes must be captured without silently corrupting existing columns.
Question 958
At Consumer finance platform, the disk spilling due to memory workflow handles loan repayment events. The problem is that loan_repayment_events_rural sort aggregation spills gigabytes of intermediates to disk. Evidence: stage metrics show spilled bytes and GC pressure on executors. Constraint: the job should improve without losing aggregation accuracy. 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?
- Right-size memory or repartition workload based on measured per-task pressure
- Disable logs and assume spilled data was never written at Consumer finance platform
- Trial an adjusted executor configuration on identical data volume
- Verify output and decreased spill plus completion time
Explanation
Correct Answer
C:Trial an adjusted executor configuration on identical data volume provides a bounded way to introduce the approved solution into loan_repayment_events_rural and detect an early mismatch. The existing signal is stage metrics show spilled bytes and GC pressure on executors; a staged change protects the service requirement (the job should improve without losing aggregation accuracy) and makes rollback practical.
Incorrect Answers
A:Right-size memory or repartition workload based on measured per-task pressure is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the loan_repayment_events_rural scenario, the observed evidence is that stage metrics show spilled bytes and GC pressure on executors; the requirement remains: the job should improve without losing aggregation accuracy.
B:Missing telemetry cannot correct memory pressure. The proposed action (Disable logs and assume spilled data was never written at Consumer finance platform) does not meet the requirement that the job should improve without losing aggregation accuracy, nor does it constitute the controlled implementation step.
D:Verify output and decreased spill plus completion time is a one-time acceptance check. It does not supply the controlled implementation step for loan_repayment_events_rural; a passing test cannot substitute for the specific task now required.
Question 959
Consider the customer_order_changes_metro workload at Online apparel cooperative: customer_order_changes_metro job points to the dev catalog even after deploying with the production target. Inspection found that configuration shows an unresolved dev catalog literal in the bundle. The governed outcome must ensure that one codebase must deploy safely to different UC environments. 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?
- Inspect resolved deployment and execute job under both targets to confirm isolation
- Monitor wrong-target resource updates and inconsistent variables for customer_order_changes_metro
- Parameterize environment-specific catalog and resources using Declarative Automation Bundle targets
- Replace the Git code with a different unreviewed copy for every environment at Online apparel cooperative
Explanation
Correct Answer
B:Monitor wrong-target resource updates and inconsistent variables for customer_order_changes_metro creates recurring visibility into the failure mode (customer_order_changes_metro job points to the dev catalog even after deploying with the production target). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while one codebase must deploy safely to different UC environments.
Incorrect Answers
A:Inspect resolved deployment and execute job under both targets to confirm isolation is a one-time acceptance check. It does not supply continuing operational detection for customer_order_changes_metro; a passing test cannot substitute for the specific task now required.
C:Parameterize environment-specific catalog and resources using Declarative Automation Bundle targets is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the customer_order_changes_metro 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.
D:Diverging codebases defeat controlled promotion. The proposed action (Replace the Git code with a different unreviewed copy for every environment at Online apparel cooperative) does not meet the requirement that one codebase must deploy safely to different UC environments, nor does it constitute continuing operational detection.
Question 960
A data engineer at Consumer finance platform is responsible for loan repayment events. The disk spilling due to memory issue is that loan_repayment_events_rural sort aggregation spills gigabytes of intermediates to disk. The supporting evidence is that stage metrics show spilled bytes and GC pressure on executors. The engineer must ensure that the job should improve without losing aggregation accuracy. 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?
- Monitor memory spill and long-GC trends for loan_repayment_events_rural
- Verify output and decreased spill plus completion time
- Disable logs and assume spilled data was never written at Consumer finance platform
- Right-size memory or repartition workload based on measured per-task pressure
Explanation
Correct Answer
A:Monitor memory spill and long-GC trends for loan_repayment_events_rural creates recurring visibility into the failure mode (loan_repayment_events_rural sort aggregation spills gigabytes of intermediates to disk). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the job should improve without losing aggregation accuracy.
Incorrect Answers
B:Verify output and decreased spill plus completion time is a one-time acceptance check. It does not supply continuing operational detection for loan_repayment_events_rural; a passing test cannot substitute for the specific task now required.
C:Missing telemetry cannot correct memory pressure. The proposed action (Disable logs and assume spilled data was never written at Consumer finance platform) does not meet the requirement that the job should improve without losing aggregation accuracy, nor does it constitute continuing operational detection.
D:Right-size memory or repartition workload based on measured per-task pressure is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the loan_repayment_events_rural scenario, the observed evidence is that stage metrics show spilled bytes and GC pressure on executors; the requirement remains: the job should improve without losing aggregation accuracy.