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An auditor reviews the applied Fabric control: Parse with an explicit schema and route malformed rows to a quarantine output. It was selected to address: A streaming source emits JSON with an optional temperature field and parsing failures terminate the job. Which evidence demonstrates the intended result?
Separating invalid records from typed valid rows allows streaming jobs to continue safely.
Overlapping hopping windows recompute aggregates over sliding intervals. It does not show that a malformed test record is quarantined while valid events remain queryable.
The stream must have an active compatible destination for events to be materialized there. It does not show that a malformed test record is quarantined while valid events remain queryable.
Native tables store ingested data inside the KQL database for efficient query patterns. It does not show that a malformed test record is quarantined while valid events remain queryable.
A Fabric data engineer receives a change request: A nightly pipeline must not send a completion notice if the data quality notebook fails. Which action best produces this measurable result: the success notice appears only after validation and the failure notice carries the error when validation fails?
Dependency outcomes prevent false operational success claims. Verify that the success notice appears only after validation and the failure notice carries the error when validation fails.
Dataflow Gen2 provides visual ingestion/transformation, reducing the need for custom Spark code. However, this alone does not show that the success notice appears only after validation and the failure notice carries the error when validation fails.
Warehouse destinations in Dataflow Gen2 can require staging before the destination write. However, this alone does not show that the success notice appears only after validation and the failure notice carries the error when validation fails.
Query transformations and data destination settings are separate deployment concerns. However, this alone does not show that the success notice appears only after validation and the failure notice carries the error when validation fails.
The reviewer will approve this deployment only when it fixes both issues: (a) A dashboard must show failed source refreshes across lakehouses and warehouses without granting operators write access. (b) A warehouse analyst wants recent failed and canceled SQL statements correlated to users. Which proposed pair of changes is appropriate?
Step 1 resolves requirement A: Monitoring visibility can be separated from authoring or item modification privileges. Step 2 resolves requirement B: SQL query monitoring provides query-level facts rather than only Fabric item health. Both acceptance tests are required: an observer sees relevant failures but cannot change pipeline definitions; and the selected canceled query is traced to its recorded request and user.
Monitoring visibility can be separated from authoring or item modification privileges. SQL query monitoring provides query-level facts rather than only Fabric item health. The proposed steps (Open the notebook/Spark application run details and relevant driver or executor logs; compare multiple refresh-history durations and per-query execution behavior) address other capabilities instead of this required pair.
Monitoring visibility can be separated from authoring or item modification privileges. The other proposed action (compare multiple refresh-history durations and per-query execution behavior) addresses a different operation. SQL query monitoring provides query-level facts rather than only Fabric item health.
SQL query monitoring provides query-level facts rather than only Fabric item health. The other proposed action (Open the notebook/Spark application run details and relevant driver or executor logs) does not implement the first control. Monitoring visibility can be separated from authoring or item modification privileges.
A Fabric engineer has implemented the following change: Filter or quarantine invalid keys and publish data-quality results before merging into silver. The original requirement was: A structured table has an abnormal count of null product IDs after a CSV import. Which observation best validates that the change works?
Ingestion validation separates bad source rows from trustworthy analytic data.
Mirroring is a replication pattern, not a general bidirectional transaction editor. It does not show that rows with null keys are excluded or repaired according to policy and counted.
Managed gateway connectivity enables approved on-premises source access for supported connectors. It does not show that rows with null keys are excluded or repaired according to policy and counted.
Flattening nested structures creates the relational schema required by T-SQL consumers. It does not show that rows with null keys are excluded or repaired according to policy and counted.
An auditor reviews the applied Fabric control: Configure a pipeline schedule with correct timezone and recurrence. It was selected to address: A finance ingestion must run at 02:00 daily with no external source event signal. Which evidence demonstrates the intended result?
Scheduled triggers execute a workflow at defined times independent of source change events.
Warehouse destinations in Dataflow Gen2 can require staging before the destination write. It does not show that run history contains the expected daily occurrence at the configured schedule.
Spark code supports programmable distributed transforms and Delta upsert patterns. It does not show that run history contains the expected daily occurrence at the configured schedule.
Query transformations and data destination settings are separate deployment concerns. It does not show that run history contains the expected daily occurrence at the configured schedule.
A Fabric engineer has implemented the following change: Add the supported narrowly scoped data-connection rule or managed private endpoint for the approved target. The original requirement was: An approved OneLake cross-workspace connection stopped working immediately after outbound access protection was enabled. Which observation best validates that the change works?
Outbound access protection blocks destinations by default until a permitted exception is configured.
Domain metadata and endorsement communicate ownership and trust, not write grants. It does not show that the specific approved connection succeeds while unrelated external targets remain blocked.
Starter pools can reduce Spark session startup cost compared with capacity-level custom pools. It does not show that the specific approved connection succeeds while unrelated external targets remain blocked.
An environment can override workspace compute only when the administrator permits per-item customization. It does not show that the specific approved connection succeeds while unrelated external targets remain blocked.
An auditor reviews the applied Fabric control: Use supported connection references or environment binding rules and keep credentials in the destination's governed store. It was selected to address: A deployment must preserve secret values while moving item definitions into a test environment. Which evidence demonstrates the intended result?
Source-controlled definitions should not embed reusable production secrets.
Branch-based review resolves competing definition edits before a shared release branch is updated. It does not show that the test item authenticates with approved test credentials and repository history contains no secrets.
A Git merge does not necessarily update every connected workspace or deployment stage. It does not show that the test item authenticates with approved test credentials and repository history contains no secrets.
Reverting item definitions is a separate action from restoring underlying data that may have changed. It does not show that the test item authenticates with approved test credentials and repository history contains no secrets.
The data platform team needs a narrowly scoped fix: KQL queries over a frequently reused Delta shortcut are too slow, but the source should remain in OneLake. Which approach satisfies the documented test that the benchmark shows improved query latency with source freshness inside the approved window?
Query acceleration caches relevant shortcut data for faster queries while retaining source storage. Verify that the benchmark shows improved query latency with source freshness inside the approved window.
Streaming imposes state and always-on operation costs that a finite batch task may not need. However, this alone does not show that the benchmark shows improved query latency with source freshness inside the approved window.
Tumbling windows partition time into fixed, nonoverlapping intervals. However, this alone does not show that the benchmark shows improved query latency with source freshness inside the approved window.
Checkpoint compatibility depends on sources, grouping keys, operators and state schema. However, this alone does not show that the benchmark shows improved query latency with source freshness inside the approved window.
The project has two blockers. Blocker A: A Dataflow Gen2 refresh fails with a Power Query conversion error because an amount column now contains the string N/A in several source rows. Blocker B: A T-SQL MERGE job fails due to multiple source rows matching one target business key. What pair of actions resolves both blockers?
Step 1 resolves requirement A: Invalid source text causes a deterministic type-conversion failure that extra retries or staging changes cannot repair. Step 2 resolves requirement B: Conflicting source matches prevent unambiguous one-target-row updates. Both acceptance tests are required: rows with valid amounts load as numbers and invalid source values are captured for remediation; and the merge updates each target key once and produces the expected latest value.
Invalid source text causes a deterministic type-conversion failure that extra retries or staging changes cannot repair. The other proposed action (align destination decimal precision/scale and validate source data before copying) addresses a different operation. Conflicting source matches prevent unambiguous one-target-row updates.
Conflicting source matches prevent unambiguous one-target-row updates. The other proposed action (Fix the supported ingestion mapping or source timestamp format and test typed conversion) does not implement the first control. Invalid source text causes a deterministic type-conversion failure that extra retries or staging changes cannot repair.
Invalid source text causes a deterministic type-conversion failure that extra retries or staging changes cannot repair. Conflicting source matches prevent unambiguous one-target-row updates. The proposed steps (Fix the supported ingestion mapping or source timestamp format and test typed conversion; align destination decimal precision/scale and validate source data before copying) address other capabilities instead of this required pair.
A shared Fabric backlog includes two mandatory controls. First: An existing operational database needs near-real-time analytical copies without a hand-built polling ETL pipeline. Second: A Dataflow Gen2 query is configured for Warehouse output but staging is disabled, blocking destination configuration. Which two-part implementation satisfies them together?
Step 1 resolves requirement A: Mirroring replicates supported source changes into Fabric with managed synchronization. Step 2 resolves requirement B: Warehouse dataflow destinations can depend on an intermediate staging path. Both acceptance tests are required: an inserted and updated source row appear after the expected replication delay; and the dataflow accepts the warehouse destination and refreshes successfully.
Mirroring replicates supported source changes into Fabric with managed synchronization. Warehouse dataflow destinations can depend on an intermediate staging path. The proposed steps (Choose a Fabric Warehouse for the SQL-oriented dimensional serving workload; use a supported external shortcut if read-through access meets the governance and performance needs) address other capabilities instead of this required pair.
Mirroring replicates supported source changes into Fabric with managed synchronization. The other proposed action (use a supported external shortcut if read-through access meets the governance and performance needs) addresses a different operation. Warehouse dataflow destinations can depend on an intermediate staging path.
Warehouse dataflow destinations can depend on an intermediate staging path. The other proposed action (Choose a Fabric Warehouse for the SQL-oriented dimensional serving workload) does not implement the first control. Mirroring replicates supported source changes into Fabric with managed synchronization.
The operations team has applied: Inspect the pipeline run and its activity-level details in the supported Monitoring hub. Its purpose was: A customer pipeline failed overnight and operators need the exact failing Copy activity, duration and source error. Which of the following provides the strongest direct evidence of success?
Run-level status does not replace individual activity diagnostics for failure localization.
Editing/publishing validation and scheduled refresh are distinct operational states. It does not show that the report identifies the failing activity, run ID, error and elapsed time.
Notebook failures can originate in the Spark job rather than pipeline orchestration. It does not show that the report identifies the failing activity, run ID, error and elapsed time.
Queue wait time and execution time require different capacity and performance actions. It does not show that the report identifies the failing activity, run ID, error and elapsed time.
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