Databricks Certified Data Engineer Associate Practice Test 19
Question 180
At Independent cinema group, the job conditional branching workflow handles ticket transactions. The problem is that ticket_transactions_coastal quality validation flags an empty input but the pipeline always publishes gold. Evidence: the job DAG lacks an if/else decision based on validation outcome. Constraint: empty invalid batches must skip publication while still reporting status. 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 Lakeflow condition task to route pass and fail paths explicitly
- Always run publish regardless of validator outcome at Independent cinema group
- Identify the condition output and branch decisions required for ticket_transactions_coastal
- Monitor branch outcomes and unexpected publish-after-failure events for ticket_transactions_coastal
Explanation
Correct Answer
A:Use a Lakeflow condition task to route pass and fail paths explicitly is the intended durable approach for ticket_transactions_coastal: it addresses the verified problem (ticket_transactions_coastal quality validation flags an empty input but the pipeline always publishes gold) while preserving the required behavior (empty invalid batches must skip publication while still reporting status). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
B:Unconditional publication violates the quality gate. The proposed action (Always run publish regardless of validator outcome at Independent cinema group) does not meet the requirement that empty invalid batches must skip publication while still reporting status, nor does it constitute the target approach.
C:Identify the condition output and branch decisions required for ticket_transactions_coastal could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The ticket_transactions_coastal workflow still requires that empty invalid batches must skip publication while still reporting status.
D:Monitor branch outcomes and unexpected publish-after-failure events for ticket_transactions_coastal would help detect future recurrence, but metrics alone do not deliver the target approach. The ticket_transactions_coastal requirement is that empty invalid batches must skip publication while still reporting status.
Question 181
A data engineer at Research clinical trial group is responsible for consent-related data changes. The conditional flag when otherwise issue is that consent_related_data_changes_urban rows have statuses requiring a three-way risk category. The supporting evidence is that a simple boolean expression sends null status to a high-risk category. The engineer must ensure that business rules distinguish active, cancelled and unknown statuses. 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?
- Treat null as an active subscription without evidence at Research clinical trial group
- Use when/otherwise with explicit conditions and an unknown default
- Enumerate source states and null handling for the consent_related_data_changes_urban flag
- Deploy a deterministic mapping table and validate the input states
Explanation
Correct Answer
C:Enumerate source states and null handling for the consent_related_data_changes_urban flag directly investigates the evidence (a simple boolean expression sends null status to a high-risk category) and distinguishes possible causes of consent_related_data_changes_urban rows have statuses requiring a three-way risk category. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: business rules distinguish active, cancelled and unknown statuses.
Incorrect Answers
A:Missing status cannot be assumed to mean active. The proposed action (Treat null as an active subscription without evidence at Research clinical trial group) does not meet the requirement that business rules distinguish active, cancelled and unknown statuses, nor does it constitute the required pre-change investigation.
B:Use when/otherwise with explicit conditions and an unknown default is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the consent_related_data_changes_urban scenario, the observed evidence is that a simple boolean expression sends null status to a high-risk category; the requirement remains: business rules distinguish active, cancelled and unknown statuses.
D:Deploy a deterministic mapping table and validate the input states 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 a simple boolean expression sends null status to a high-risk category.
Question 182
At Agricultural credit union, the file arrival trigger workflow handles farm-loan transaction history. The problem is that farm_loan_transaction_history_coastal job runs hourly although only one file arrives most days. Evidence: execution history shows repeated empty runs with compute startup cost. Constraint: process each new delivered file promptly without idle polling. 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?
- Use a supported file-arrival trigger for the eligible storage location
- Run a full pipeline every minute even if no files arrive at Agricultural credit union
- Enable trigger in staging and test a new object arrival
- Upload a test file and confirm exactly the expected run fires
Explanation
Correct Answer
C:Enable trigger in staging and test a new object arrival provides a bounded way to introduce the approved solution into farm_loan_transaction_history_coastal and detect an early mismatch. The existing signal is execution history shows repeated empty runs with compute startup cost; a staged change protects the service requirement (process each new delivered file promptly without idle polling) and makes rollback practical.
Incorrect Answers
A:Use a supported file-arrival trigger for the eligible storage location is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the farm_loan_transaction_history_coastal scenario, the observed evidence is that execution history shows repeated empty runs with compute startup cost; the requirement remains: process each new delivered file promptly without idle polling.
B:Repetitive empty executions waste compute and cost. The proposed action (Run a full pipeline every minute even if no files arrive at Agricultural credit union) does not meet the requirement that process each new delivered file promptly without idle polling, nor does it constitute the controlled implementation step.
D:Upload a test file and confirm exactly the expected run fires is a one-time acceptance check. It does not supply the controlled implementation step for farm_loan_transaction_history_coastal; a passing test cannot substitute for the specific task now required.
Question 183
A data engineer at Clinical diagnostics network is responsible for lab sample events. The approximate distinct count issue is that lab_sample_events_urban serves an exploratory dashboard counting hundreds of millions of unique session IDs. The supporting evidence is that exact count-distinct creates high aggregation cost during interactive prototyping. The engineer must ensure that users explicitly accept bounded approximation in exchange for speed. 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?
- Compare estimate error and latency to the agreed tolerance
- Substitute sum(session_id) as an estimate of unique sessions at Clinical diagnostics network
- Monitor relative error on sampled exact baselines for lab_sample_events_urban
- Use approx_count_distinct for approximate high-cardinality distinct estimates
Explanation
Correct Answer
C:Monitor relative error on sampled exact baselines for lab_sample_events_urban creates recurring visibility into the failure mode (lab_sample_events_urban serves an exploratory dashboard counting hundreds of millions of unique session IDs). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while users explicitly accept bounded approximation in exchange for speed.
Incorrect Answers
A:Compare estimate error and latency to the agreed tolerance 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.
B:Adding identifiers is not a distinct-count estimator. The proposed action (Substitute sum(session_id) as an estimate of unique sessions at Clinical diagnostics network) does not meet the requirement that users explicitly accept bounded approximation in exchange for speed, nor does it constitute continuing operational detection.
D:Use approx_count_distinct for approximate high-cardinality distinct estimates 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 exact count-distinct creates high aggregation cost during interactive prototyping; the requirement remains: users explicitly accept bounded approximation in exchange for speed.
Question 184
A data engineer at Regional museum alliance is responsible for artifact metadata updates. The MERGE key update issue is that artifact_metadata_updates_metro 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 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 ambiguous matches and merge row-change counts for artifact_metadata_updates_metro
- MERGE with multiple unfiltered source matches per target key at Regional museum alliance
- Verify one current row per ID and updated values after retries
- Use Delta MERGE with a deduplicated source on invoice_id and matched update logic
Explanation
Correct Answer
A:Monitor ambiguous matches and merge row-change counts for artifact_metadata_updates_metro creates recurring visibility into the failure mode (artifact_metadata_updates_metro delta target must apply corrected invoice amounts from an incremental feed). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while target must have one latest value per invoice after applying ordered changes.
Incorrect Answers
B:Ambiguous multiple source matches can make updates nondeterministic or fail. The proposed action (MERGE with multiple unfiltered source matches per target key at Regional museum alliance) does not meet the requirement that target must have one latest value per invoice after applying ordered changes, nor does it constitute continuing operational detection.
C:Verify one current row per ID and updated values after retries is a one-time acceptance check. It does not supply continuing operational detection for artifact_metadata_updates_metro; a passing test cannot substitute for the specific task now required.
D:Use Delta MERGE with a deduplicated source on invoice_id and matched update logic is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the artifact_metadata_updates_metro scenario, the observed evidence is that the source has two updates for the same invoice_id in one batch; the requirement remains: target must have one latest value per invoice after applying ordered changes.
Question 185
The harvest_purchase_orders_west pipeline at National farm supplier has this failure: harvest_purchase_orders_west silver records pass ingestion despite negative billed quantities. The team observed that validation sample identifies impossible values in otherwise well-formed JSON. Business requirement: bad records need a defined reject/quarantine policy without hiding valid data. 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 expectation violation counts and changed data quality trends in harvest_purchase_orders_west
- Inject invalid rows and verify correct drop, fail or quarantine behavior
- Define explicit data-quality expectations with documented action for invalid records
- Delete invalid rows silently and report the entire batch as error-free at National farm supplier
Explanation
Correct Answer
A:Monitor expectation violation counts and changed data quality trends in harvest_purchase_orders_west creates recurring visibility into the failure mode (harvest_purchase_orders_west silver records pass ingestion despite negative billed quantities). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while bad records need a defined reject/quarantine policy without hiding valid data.
Incorrect Answers
B:Inject invalid rows and verify correct drop, fail or quarantine behavior is a one-time acceptance check. It does not supply continuing operational detection for harvest_purchase_orders_west; a passing test cannot substitute for the specific task now required.
C:Define explicit data-quality expectations with documented action for invalid records is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the harvest_purchase_orders_west scenario, the observed evidence is that validation sample identifies impossible values in otherwise well-formed JSON; the requirement remains: bad records need a defined reject/quarantine policy without hiding valid data.
D:Silent loss hides quality issues and masks upstream defects. The proposed action (Delete invalid rows silently and report the entire batch as error-free at National farm supplier) does not meet the requirement that bad records need a defined reject/quarantine policy without hiding valid data, nor does it constitute continuing operational detection.
Question 186
A data engineer at Satellite imagery startup is responsible for land-cover observations. The Lakeflow Connect standard connector issue is that a land_cover_observations_island source has a compatible connector but existing custom scripts have divergent retries. The supporting evidence is that logs show different authentication and pagination paths across team-owned scripts. The engineer must ensure that ingestion must be standardized under governed destinations. 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?
- Use the supported Lakeflow Connect standard connector with scoped source access
- Let every notebook invent a new unscheduled direct source sync at Satellite imagery startup
- Compare loaded rows and source bookmarks before switching production
- Monitor source offset, failed pages and connector task errors for land_cover_observations_island
Explanation
Correct Answer
D:Monitor source offset, failed pages and connector task errors for land_cover_observations_island creates recurring visibility into the failure mode (a land_cover_observations_island source has a compatible connector but existing custom scripts have divergent retries). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while ingestion must be standardized under governed destinations.
Incorrect Answers
A:Use the supported Lakeflow Connect standard connector with scoped source access is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the land_cover_observations_island scenario, the observed evidence is that logs show different authentication and pagination paths across team-owned scripts; the requirement remains: ingestion must be standardized under governed destinations.
B:Uncoordinated custom pulls are less governed and harder to recover. The proposed action (Let every notebook invent a new unscheduled direct source sync at Satellite imagery startup) does not meet the requirement that ingestion must be standardized under governed destinations, nor does it constitute continuing operational detection.
C:Compare loaded rows and source bookmarks before switching production is a one-time acceptance check. It does not supply continuing operational detection for land_cover_observations_island; a passing test cannot substitute for the specific task now required.
Question 187
A data engineer at Online apparel cooperative is responsible for customer order changes. The bundle target override issue is that customer_order_changes_metro job points to the dev catalog even after deploying with the production target. The supporting evidence is that configuration shows an unresolved dev catalog literal in the bundle. The engineer must ensure that one codebase must deploy safely to different UC environments. 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?
- Inspect resolved deployment and execute job under both targets to confirm isolation
- Replace the Git code with a different unreviewed copy for every environment at Online apparel cooperative
- Add tested prod variable overrides and run validation before deploy
- Inspect bundle variables, target overrides and resolved job config for customer_order_changes_metro
Explanation
Correct Answer
A:Inspect resolved deployment and execute job under both targets to confirm isolation directly tests the behavior that should change following the correction. With the observed evidence (configuration shows an unresolved dev catalog literal in the bundle), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that 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 Online apparel cooperative) does not meet the requirement that one codebase must deploy safely to different UC environments, nor does it constitute the post-change acceptance test.
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 post-change acceptance test, especially given the evidence that configuration shows an unresolved dev catalog literal in the bundle. This matters here because a data engineer at Online apparel cooperative is responsible for customer order changes. The bundle target overrideā¦.
D:Inspect bundle variables, target overrides and resolved job config for customer_order_changes_metro could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The customer_order_changes_metro workflow still requires that one codebase must deploy safely to different UC environments.
Question 188
A data engineer at National heritage library is responsible for digitization inventories. The source method selection issue is that the digitization_inventories_south producer is a managed enterprise database but engineers plan a custom nightly file scraper. The supporting evidence is that evaluation finds supported managed CDC connector and tight freshness targets. The engineer must ensure that data must reach Unity Catalog with near-real-time change capture. 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?
- Use monthly manual CSV downloads for a near-real-time feed at National heritage library
- Compare connector support, freshness SLA, cost and source load for digitization_inventories_south
- Select Lakeflow Connect managed CDC rather than custom file snapshots where supported
- Pilot managed CDC for a bounded table before removing the nightly export
Explanation
Correct Answer
B:Compare connector support, freshness SLA, cost and source load for digitization_inventories_south directly investigates the evidence (evaluation finds supported managed CDC connector and tight freshness targets) and distinguishes possible causes of the digitization_inventories_south producer is a managed enterprise database but engineers plan a custom nightly file scraper. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: data must reach Unity Catalog with near-real-time change capture.
Incorrect Answers
A:Manual batch exports cannot meet continuous change freshness. The proposed action (Use monthly manual CSV downloads for a near-real-time feed at National heritage library) does not meet the requirement that data must reach Unity Catalog with near-real-time change capture, nor does it constitute the required pre-change investigation.
C:Select Lakeflow Connect managed CDC rather than custom file snapshots where supported is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the digitization_inventories_south scenario, the observed evidence is that evaluation finds supported managed CDC connector and tight freshness targets; the requirement remains: data must reach Unity Catalog with near-real-time change capture.
D:Pilot managed CDC for a bounded table before removing the nightly export 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 evaluation finds supported managed CDC connector and tight freshness targets.
Question 189
At Clinical diagnostics network, the lab sample events workflow depends on lab_sample_events_delta. Engineers report that lab_sample_events_delta delta target must apply corrected invoice amounts from an incremental feed; the evidence is that the source has two updates for the same invoice_id in one batch. They require that target must have one latest value per invoice after applying ordered changes. 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?
- Verify one current row per ID and updated values after retries
- MERGE with multiple unfiltered source matches per target key at Clinical diagnostics network
- Test MERGE on a small target and rerun an identical source batch
- Identify stable merge keys and deduplicate multiple updates in the batch for lab_sample_events_delta
Explanation
Correct Answer
A:Verify one current row per ID and updated values after retries directly tests the behavior that should change after the correction. With the observed evidence (the source has two updates for the same invoice_id in one batch), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that target must have one latest value per invoice after applying ordered changes.
Incorrect Answers
B: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 post-change acceptance test.
C:Test MERGE on a small target and rerun an identical source batch 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 the source has two updates for the same invoice_id in one batch.
D: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 post-change acceptance test now requested. The lab_sample_events_delta workflow still requires that target must have one latest value per invoice after applying ordered changes.
Question 190
At Public transport authority, the streaming dedup and watermarks workflow handles fare validation events. The problem is that mobile fare_validation_events_east events arrive late and sometimes duplicate within an event-time window. Evidence: several event IDs reappear after an offline device reconnect. Constraint: the stream must remove duplicates without retaining infinite state. 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?
- Retain every key forever in unbounded streaming state at Public transport authority
- Inject duplicate and late events and verify the defined retention tradeoff
- Deduplicate with stable event IDs and a bounded event-time watermark
- Monitor late-drop counts, state-store size and duplicate output for fare_validation_events_east
Explanation
Correct Answer
D:Monitor late-drop counts, state-store size and duplicate output for fare_validation_events_east creates recurring visibility into the failure mode (mobile fare_validation_events_east events arrive late and sometimes duplicate within an event-time window). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the stream must remove duplicates without retaining infinite state.
Incorrect Answers
A:Unbounded state eventually destabilizes a long-running stream. The proposed action (Retain every key forever in unbounded streaming state at Public transport authority) does not meet the requirement that the stream must remove duplicates without retaining infinite state, nor does it constitute continuing operational detection.
B:Inject duplicate and late events and verify the defined retention tradeoff is a one-time acceptance check. It does not supply continuing operational detection for fare_validation_events_east; a passing test cannot substitute for the specific task now required.
C:Deduplicate with stable event IDs and a bounded event-time watermark is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the fare_validation_events_east scenario, the observed evidence is that several event IDs reappear after an offline device reconnect; the requirement remains: the stream must remove duplicates without retaining infinite state.