Databricks Certified Data Engineer Associate Practice Test 23
Question 220
Consider the warehouse_movement_logs_north workload at Multinational parts distributor: warehouse_movement_logs_north SQL filter misses transactions where the nullable flag was never populated. Inspection found that the predicate uses flag = NULL and always yields unknown. The governed outcome must ensure that the analysis must distinguish missing from explicitly false flag values. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which staged rollout best preserves the existing workload?
- Test null, false and true rows against the intended filter
- Use IS NULL for missing flags and IS NOT NULL for populated fields
- Replace equality-to-null filters with tested null-aware predicates
- Use flag = NULL and assume it matches missing values at Multinational parts distributor
Explanation
Correct Answer
C:Replace equality-to-null filters with tested null-aware predicates provides a bounded way to introduce the approved solution into warehouse_movement_logs_north and detect an early mismatch. The existing signal is the predicate uses flag = NULL and always yields unknown; a staged change protects the service requirement (the analysis must distinguish missing from explicitly false flag values) and makes rollback practical.
Incorrect Answers
A:Test null, false and true rows against the intended filter 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:Use IS NULL for missing flags and IS NOT NULL for populated fields 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 the predicate uses flag = NULL and always yields unknown; the requirement remains: the analysis must distinguish missing from explicitly false flag values.
D:Sql equality against null is not true. The proposed action (Use flag = NULL and assume it matches missing values at Multinational parts distributor) does not meet the requirement that the analysis must distinguish missing from explicitly false flag values, nor does it constitute the controlled implementation step.
Question 221
The payment_authorization_records_east pipeline at E-commerce payments provider has this failure: payment_authorization_records_east job fails before any Spark task begins. The team observed that cluster event log shows an unavailable instance type in the selected region. Business requirement: the diagnostic must distinguish compute provisioning failure from ETL code defects. 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?
- Start a fresh cluster then execute one representative task successfully
- Test alternate eligible compute provisioning and controlled job retry
- Select a supported compute configuration or serverless option that meets the job constraints
- Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider
Explanation
Correct Answer
B:Test alternate eligible compute provisioning and controlled job retry provides a bounded way to introduce the approved solution into payment_authorization_records_east and detect an early mismatch. The existing signal is cluster event log shows an unavailable instance type in the selected region; a staged change protects the service requirement (the diagnostic must distinguish compute provisioning failure from ETL code defects) and makes rollback practical.
Incorrect Answers
A:Start a fresh cluster then execute one representative task successfully is a one-time acceptance check. It does not supply the controlled implementation step for payment_authorization_records_east; a passing test cannot substitute for the specific task now required.
C:Select a supported compute configuration or serverless option that meets the job constraints is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the payment_authorization_records_east scenario, the observed evidence is that cluster event log shows an unavailable instance type in the selected region; the requirement remains: the diagnostic must distinguish compute provisioning failure from ETL code defects.
D:Query changes cannot fix unavailable compute capacity. The proposed action (Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider) does not meet the requirement that the diagnostic must distinguish compute provisioning failure from ETL code defects, nor does it constitute the controlled implementation step.
Question 222
The borrower_circulation_events_coastal pipeline at City library association has this failure: mobile borrower_circulation_events_coastal events arrive late and sometimes duplicate within an event-time window. The team observed that several event IDs reappear after an offline device reconnect. Business requirement: the stream must remove duplicates without retaining infinite state. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What test most directly proves the requirement is satisfied?
- Test streaming replay with simulated delay and state checkpointing
- Inject duplicate and late events and verify the defined retention tradeoff
- Measure late-arrival distribution and validate event IDs and timestamps for borrower_circulation_events_coastal
- Retain every key forever in unbounded streaming state at City library association
Explanation
Correct Answer
B:Inject duplicate and late events and verify the defined retention tradeoff directly tests the behavior that should change after the correction. With the observed evidence (several event IDs reappear after an offline device reconnect), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the stream must remove duplicates without retaining infinite state.
Incorrect Answers
A:Test streaming replay with simulated delay and state checkpointing 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 several event IDs reappear after an offline device reconnect.
C: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 post-change acceptance test now requested. The borrower_circulation_events_coastal workflow still requires that the stream must remove duplicates without retaining infinite state.
D: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 post-change acceptance test.
Question 223
At Online apparel cooperative, the table SELECT least privilege workflow handles customer order changes. The problem is that customer_order_changes_west contractor group needs read-only curated aggregates but can edit source tables. Evidence: privilege audit shows broad write grants inherited from a project role. Constraint: group must query approved output without data modification. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which investigation is the strongest first step?
- Grant SELECT on approved table and remove unnecessary write permissions
- Grant ALL PRIVILEGES on the entire catalog to a read-only group at Online apparel cooperative
- Replace broad grants through a staged permission change with rollback
- Identify group membership, inherited privileges and accessible tables for customer_order_changes_west
Explanation
Correct Answer
D:Identify group membership, inherited privileges and accessible tables for customer_order_changes_west directly investigates the evidence (privilege audit shows broad write grants inherited from a project role) and distinguishes possible causes of customer_order_changes_west contractor group needs read-only curated aggregates but can edit source tables. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: group must query approved output without data modification.
Incorrect Answers
A:Grant SELECT on approved table and remove unnecessary write permissions is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the customer_order_changes_west scenario, the observed evidence is that privilege audit shows broad write grants inherited from a project role; the requirement remains: group must query approved output without data modification.
B:All privileges violate read-only requirement. The proposed action (Grant ALL PRIVILEGES on the entire catalog to a read-only group at Online apparel cooperative) does not meet the requirement that group must query approved output without data modification, nor does it constitute the required pre-change investigation.
C:Replace broad grants through a staged permission change with rollback 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 privilege audit shows broad write grants inherited from a project role. Here, the relevant situation is: the table SELECT least privilege workflow handles customer order changes. The problem is that….
Question 224
A data engineer at Manufacturing quality network is responsible for factory defect records. The quality expectations pipeline issue is that factory_defect_records_urban silver records pass ingestion despite negative billed quantities. The supporting evidence is that validation sample identifies impossible values in otherwise well-formed JSON. The engineer must ensure that bad records need a defined reject/quarantine policy without hiding valid data. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. What is the safest migration or deployment sequence?
- Inject invalid rows and verify correct drop, fail or quarantine behavior
- Delete invalid rows silently and report the entire batch as error-free at Manufacturing quality network
- Define explicit data-quality expectations with documented action for invalid records
- Roll out expectation checks and a quarantine audit before enforcing production policy
Explanation
Correct Answer
D:Roll out expectation checks and a quarantine audit before enforcing production policy provides a bounded way to introduce the approved solution into factory_defect_records_urban and detect an early mismatch. The existing signal is validation sample identifies impossible values in otherwise well-formed JSON; a staged change protects the service requirement (bad records need a defined reject/quarantine policy without hiding valid data) and makes rollback practical.
Incorrect Answers
A:Inject invalid rows and verify correct drop, fail or quarantine behavior is a one-time acceptance check. It does not supply the controlled implementation step for factory_defect_records_urban; a passing test cannot substitute for the specific task now required.
B: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 Manufacturing quality network) does not meet the requirement that bad records need a defined reject/quarantine policy without hiding valid data, nor does it constitute the controlled implementation step.
C:Define explicit data-quality expectations with documented action for invalid records is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the factory_defect_records_urban 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.
Question 225
At Regional sporting venue, the column masking PII workflow handles admission scan events. The problem is that admission_scan_events_north table exposes national IDs to analysts who need only transaction amounts. Evidence: query review shows raw identifier values in common reports. Constraint: users without an approved role must see masked sensitive columns. 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?
- Apply Unity Catalog column masks or suitable centrally governed masking policy
- Monitor new PII columns, mask failures and unapproved policy changes for admission_scan_events_north
- Identify sensitive attributes, entitled roles and current query exposure for admission_scan_events_north
- Rename identifier column to a harmless label while leaving values visible at Regional sporting venue
Explanation
Correct Answer
A:Apply Unity Catalog column masks or suitable centrally governed masking policy is the intended durable approach for admission_scan_events_north: it addresses the verified problem (admission_scan_events_north table exposes national IDs to analysts who need only transaction amounts) while preserving the required behavior (users without an approved role must see masked sensitive columns). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
B:Monitor new PII columns, mask failures and unapproved policy changes for admission_scan_events_north would help detect future recurrence, but metrics alone do not deliver the target approach. The admission_scan_events_north requirement is that users without an approved role must see masked sensitive columns.
C:Identify sensitive attributes, entitled roles and current query exposure for admission_scan_events_north could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The admission_scan_events_north workflow still requires that users without an approved role must see masked sensitive columns.
D:Renaming a column does not protect its contents. The proposed action (Rename identifier column to a harmless label while leaving values visible at Regional sporting venue) does not meet the requirement that users without an approved role must see masked sensitive columns, nor does it constitute the target approach.
Question 226
The admission_scan_events_central pipeline at Regional sporting venue has this failure: admission_scan_events_central contains duplicate message IDs after file retries. The team observed that two rows share event_id but have different ingestion timestamps. Business requirement: silver needs one deterministic event per business event identifier. 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?
- Pilot a dedup transform while retaining originals in bronze for audit
- DropDuplicates on every column when duplicates differ only by ingest timestamp at Regional sporting venue
- Use deterministic row_number or dropDuplicates on the correct business key and ordering rule
- Feed repeated IDs in different order and verify the selected canonical record
Explanation
Correct Answer
A:Pilot a dedup transform while retaining originals in bronze for audit provides a bounded way to introduce the approved solution into admission_scan_events_central and detect an early mismatch. The existing signal is two rows share event_id but have different ingestion timestamps; a staged change protects the service requirement (silver needs one deterministic event per business event identifier) and makes rollback practical.
Incorrect Answers
B: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 the controlled implementation step.
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 controlled implementation step 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:Feed repeated IDs in different order and verify the selected canonical record is a one-time acceptance check. It does not supply the controlled implementation step for admission_scan_events_central; a passing test cannot substitute for the specific task now required.
Question 227
Consider the warehouse_movement_logs_metro workload at Multinational parts distributor: warehouse_movement_logs_metro bundle deployment fails after someone changes its job task reference. Inspection found that CLI output identifies invalid resource or variable configuration. The governed outcome must ensure that the error must be caught before production resources change. 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?
- Monitor validation failures and unsupported resource configuration in warehouse_movement_logs_metro
- Inspect bundle manifest, resource paths and reported validator errors for warehouse_movement_logs_metro
- Always run bundle deploy despite failing validation at Multinational parts distributor
- Include `databricks bundle validate -t prod` before deployment
Explanation
Correct Answer
D:Include `databricks bundle validate -t prod` before deployment is the intended durable approach for warehouse_movement_logs_metro: it addresses the verified problem (warehouse_movement_logs_metro bundle deployment fails after someone changes its job task reference) while preserving the required behavior (the error must be caught before production resources change). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Monitor validation failures and unsupported resource configuration in warehouse_movement_logs_metro would help detect future recurrence, but metrics alone do not deliver the target approach. The warehouse_movement_logs_metro requirement is that the error must be caught before production resources change.
B:Inspect bundle manifest, resource paths and reported validator errors for warehouse_movement_logs_metro 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_metro workflow still requires that the error must be caught before production resources change.
C:Deploying invalid configuration bypasses the preflight gate. The proposed action (Always run bundle deploy despite failing validation at Multinational parts distributor) does not meet the requirement that the error must be caught before production resources change, nor does it constitute the target approach.
Question 228
At Veterinary clinic association, the Lakeflow Connect managed connector workflow handles treatment billing events. The problem is that a treatment_billing_events_delta enterprise SaaS table requires recurring ingestion but the team maintains a brittle custom API crawler. Evidence: API tokens expire and source field names change without ingestion alerts. Constraint: the source must arrive in governed Delta tables with manageable credential rotation. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. Which test should pass before the new flow is accepted?
- Update a source row and verify correct incremental destination behavior
- Assess managed connector source support, permissions and refresh semantics for treatment_billing_events_delta
- Copy API secrets into a widely shared notebook and paste full responses manually at Veterinary clinic association
- Configure source credentials and destination catalog for a pilot sync
Explanation
Correct Answer
A:Update a source row and verify correct incremental destination behavior directly tests the behavior that should change following the correction. With the observed evidence (API tokens expire and source field names change without ingestion alerts), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the source must arrive in governed Delta tables with manageable credential rotation.
Incorrect Answers
B:Assess managed connector source support, permissions and refresh semantics for treatment_billing_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 treatment_billing_events_delta workflow still requires that the source must arrive in governed Delta tables with manageable credential rotation.
C:Shared secrets and manual copies do not provide reliable governed ingestion. The proposed action (Copy API secrets into a widely shared notebook and paste full responses manually at Veterinary clinic association) does not meet the requirement that the source must arrive in governed Delta tables with manageable credential rotation, nor does it constitute the post-change acceptance test.
D:Configure source credentials and destination catalog for a pilot sync 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 API tokens expire and source field names change without ingestion alerts. Here, the relevant situation is: the Lakeflow Connect managed connector workflow handles treatment billing events. The problem is that a….
Question 229
At E-commerce payments provider, the payment authorization records workflow depends on payment_authorization_records_east. Engineers report that payment_authorization_records_east job fails before any Spark task begins; the evidence is that cluster event log shows an unavailable instance type in the selected region. They require that the diagnostic must distinguish compute provisioning failure from ETL code defects. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which pre-change diagnostic will resolve the uncertainty?
- Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider
- Test alternate eligible compute provisioning and controlled job retry
- Select a supported compute configuration or serverless option that meets the job constraints
- Inspect cluster event log, quotas, network and cloud capacity for payment_authorization_records_east
Explanation
Correct Answer
D:Inspect cluster event log, quotas, network and cloud capacity for payment_authorization_records_east directly investigates the evidence (cluster event log shows an unavailable instance type in the selected region) and distinguishes possible causes of payment_authorization_records_east job fails before any Spark task begins. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: the diagnostic must distinguish compute provisioning failure from ETL code defects.
Incorrect Answers
A:Query changes cannot fix unavailable compute capacity. The proposed action (Rewrite successful SQL transformations without investigating provisioning at E-commerce payments provider) does not meet the requirement that the diagnostic must distinguish compute provisioning failure from ETL code defects, nor does it constitute the required pre-change investigation.
B:Test alternate eligible compute provisioning and controlled job retry 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 cluster event log shows an unavailable instance type in the selected region.
C:Select a supported compute configuration or serverless option that meets the job constraints is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the payment_authorization_records_east scenario, the observed evidence is that cluster event log shows an unavailable instance type in the selected region; the requirement remains: the diagnostic must distinguish compute provisioning failure from ETL code defects.
Question 230
At International language school, the array explode workflow handles class enrollment data. The problem is that class_enrollment_data_west has one row per order with an array of purchased items. Evidence: the silver table counts order-level rows as product-level units. Constraint: downstream inventory reporting needs one row per element with its parent key. 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?
- Split the serialized array text on commas without parsing JSON at International language school
- Pilot nested extraction and test orders with multiple items
- Apply explode or explode_outer deliberately while retaining the order ID
- Verify element row counts and parent IDs for one-item and multi-item orders
Explanation
Correct Answer
B:Pilot nested extraction and test orders with multiple items provides a bounded way to introduce the approved solution into class_enrollment_data_west and detect an early mismatch. The existing signal is the silver table counts order-level rows as product-level units; a staged change protects the service requirement (downstream inventory reporting needs one row per element with its parent key) and makes rollback practical.
Incorrect Answers
A:String splitting is not a typed nested-array transformation. The proposed action (Split the serialized array text on commas without parsing JSON at International language school) does not meet the requirement that downstream inventory reporting needs one row per element with its parent key, nor does it constitute the controlled implementation step.
C:Apply explode or explode_outer deliberately while retaining the order ID is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the class_enrollment_data_west scenario, the observed evidence is that the silver table counts order-level rows as product-level units; the requirement remains: downstream inventory reporting needs one row per element with its parent key.
D:Verify element row counts and parent IDs for one-item and multi-item orders is a one-time acceptance check. It does not supply the controlled implementation step for class_enrollment_data_west; a passing test cannot substitute for the specific task now required.