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Inspect skewed keys and evaluate salting or adaptive skew-join behavior when appropriate is useful when one batch is dominated by a single experiment ID with millions of measurements, since a hot key can create one massive shuffle partition even with many available executors; however, the actual requirement is the DataFrame is used by four expensive downstream analyses, which calls for Persist the intermediate only when reuse and cache capacity justify it.

The action Review Spark adaptive execution and partition settings based on observed task sizes solves a shuffle creates too many tiny post-shuffle tasks because appropriate partition sizes reduce scheduler overhead without sacrificing parallelism; it does not by itself solve the DataFrame is used by four expensive downstream analyses, whereas Persist the intermediate only when reuse and cache capacity justify it does.

Applying Disable adaptive execution solely because its configuration name contains the word adaptive when the DataFrame is used by four expensive downstream analyses would introduce a defect because fabric runtimes enable AQE by default; changes should follow measured execution evidence; a direct solution is Persist the intermediate only when reuse and cache capacity justify it.

The action Record and inspect the shortcut target, credential mode and source ownership solves the storage administrator needs to establish which source system owns a shared shortcut because lineage and security review require the actual target and credential context, not merely the shortcut's display label; it does not by itself solve oneLake consumers report access denied despite seeing the shortcut name, whereas Verify both shortcut-location permissions and target-source permissions for their identity does.

Applying Copy external credentials into every notebook source cell to make OneLake shortcuts work when oneLake consumers report access denied despite seeing the shortcut name would introduce a defect because storing credentials in code creates secret exposure and does not establish proper identity governance; a direct solution is Verify both shortcut-location permissions and target-source permissions for their identity.

Option Place or register the supported Delta table under the lakehouse Tables structure would focus on the separate issue that an incoming Delta table is represented as many raw files but should appear as a managed table because the Tables area discovers Delta datasets as tables, whereas arbitrary files under Files are not automatically equivalent, not the current requirement that oneLake consumers report access denied despite seeing the shortcut name; the appropriate remedy is Verify both shortcut-location permissions and target-source permissions for their identity.

Choosing Expose production connection credentials in a public branch to make promotion reproducible would not satisfy the case condition (a developer changes an item in production that differs from the Git-reviewed revision), because source control must not become a secrets distribution mechanism; Investigate drift and restore a controlled promotion process with recorded approvals preserves the intended result.

Option Connect supported Fabric items to a Git repository and use reviewed branches would focus on the separate issue that developers need to version notebook and pipeline definitions with code review because git integration records supported item definitions and enables controlled changes before synchronization, not the current requirement that a developer changes an item in production that differs from the Git-reviewed revision; the appropriate remedy is Investigate drift and restore a controlled promotion process with recorded approvals.

The option Compare workspace and repository states before committing or updating applies to the separate issue that a workspace shows uncommitted changes despite a clean code branch, because workspace changes and repository changes are different directions of synchronization, so blind overwrite risks losing work; the current condition is a developer changes an item in production that differs from the Git-reviewed revision, which calls for Investigate drift and restore a controlled promotion process with recorded approvals.

The option Assume workspace admins always experience identical row filtering to restricted report viewers fails to meet an SQL analytics endpoint uses delegated-owner identity and refuses a secured shortcut source, given that privileged workspace access and engine identity mode can change effective data permissions; Review the identity mode and consider supported user-identity access for OneLake-filtered source data is the correct scope of action.

The option Verify the selected Direct Lake and OneLake identity integration rather than assuming every model mode is equivalent applies to the separate issue that a Power BI semantic model over SQL mode does not apply the expected producer restrictions, because semantic model access modes vary in how end-user identity is passed through to underlying data; the current condition is an SQL analytics endpoint uses delegated-owner identity and refuses a secured shortcut source, which calls for Review the identity mode and consider supported user-identity access for OneLake-filtered source data.

Test with a qualified least-privilege guest identity and verify cross-tenant configuration is useful when data owners want to validate access for a guest rather than their own administrative account, since entra guest policy and Fabric security must both permit the specific collaboration path; however, the actual requirement is an SQL analytics endpoint uses delegated-owner identity and refuses a secured shortcut source, which calls for Review the identity mode and consider supported user-identity access for OneLake-filtered source data.

The option Separate raw landing from validation and use explicit failure handling applies to the separate issue that the parsing task can fail while the raw input must remain retained, because preserving raw evidence enables correction without guessing or regenerating original input; the current condition is some files arrive twice with the same business ID, which calls for Deduplicate using the source event or file key before committing output rows.

For this requirement of some files arrive twice with the same business ID, Delete all source files as soon as the trigger fires, before validation finishes would be unsafe or ineffective because losing raw input before confirmed processing prevents safe recovery; apply Deduplicate using the source event or file key before committing output rows instead.

The action Record run outputs and per-file completion status in a durable operational table solves operations needs a count of successful and failed files by day because a single pipeline success flag does not represent a multi-file batch's actual coverage; it does not by itself solve some files arrive twice with the same business ID, whereas Deduplicate using the source event or file key before committing output rows does.

Choose the alphabetically last flight status instead of the newest source event would not satisfy the business needs both current status and an immutable audit of all transitions because lexicographic sorting has no reliable relationship to event chronology; the defensible response is Maintain separate versioned event history and a current-state projection.

Translate the source cancellation semantics into an explicit governed target status is useful when a canceled flight arrives as a special delete/status event, since cancellations must be reflected in the curated state without accidentally deleting audit history; however, the actual requirement is the business needs both current status and an immutable audit of all transitions, which calls for Maintain separate versioned event history and a current-state projection.

The action Upsert by flight identifier and source version rather than unconditional append solves only previously unseen flights should be inserted while changed statuses update existing rows because change-aware merge maintains one current row per flight when the source revises its status; it does not by itself solve the business needs both current status and an immutable audit of all transitions, whereas Maintain separate versioned event history and a current-state projection does.

For this requirement of analysts need age bands but direct birthdates should not enter the public Gold table, Interpret a null diagnosis code as an observed confirmed disease state would be unsafe or ineffective because missing clinical values are not positive evidence; apply Derive approved age groups in Silver and exclude restricted identifiers from Gold instead.

For weekly counts must use an epidemiological week derived from event date, Group validated event timestamps using the defined business week calendar can be justified because reporting-week conventions must be consistent across periods and regions; for this scenario involving analysts need age bands but direct birthdates should not enter the public Gold table, the targeted response is Derive approved age groups in Silver and exclude restricted identifiers from Gold.

Although Quarantine the record under an explicit data-quality failure rule fits the separate issue that a case report contains an invalid negative age because numeric type validation alone cannot establish medically plausible values, this case concerns analysts need age bands but direct birthdates should not enter the public Gold table and should be resolved with Derive approved age groups in Silver and exclude restricted identifiers from Gold.

The action Use KQL time filtering and grouped aggregation on the merchant and status solves a dashboard must show declined transactions by merchant over a rolling period because the event query should combine status predicates with a defined time window and business key; it does not by itself solve some source timestamps are strings with inconsistent formats, whereas Parse timestamps into KQL datetime values before binning or ordering does.

For a duplicate delivery has the same transaction ID and source revision, Deduplicate according to transaction ID and authoritative revision before counting outcomes can be justified because delivery retries are not new authorizations and would inflate declined counts; for this scenario involving some source timestamps are strings with inconsistent formats, the targeted response is Parse timestamps into KQL datetime values before binning or ordering.

The option Delete all declined events from the source to improve the approval rate shown to management fails to meet some source timestamps are strings with inconsistent formats, given that removing actual business outcomes falsifies the analytical record; Parse timestamps into KQL datetime values before binning or ordering is the correct scope of action.

Although Define a measured duration threshold relative to the workload's SLA fits the separate issue that the manager needs an alert for sustained processing delays because latency alerts should use historical and expected runtime rather than arbitrary panic thresholds, this case concerns the slowest Dataflow Gen2 query varies with month-end volume and should be resolved with Track refresh duration by query and compare source-row volumes.

Increase every scheduled job's concurrency to the maximum without observing capacity would not satisfy the slowest Dataflow Gen2 query varies with month-end volume because more simultaneous work can worsen contention and queuing; the defensible response is Track refresh duration by query and compare source-row volumes.

The option Monitor retry counts and failure categories separately from eventual success applies to the separate issue that a production workload shows frequent retries after transient source failures, because high retry rates can threaten SLAs even when the final run status is green; the current condition is the slowest Dataflow Gen2 query varies with month-end volume, which calls for Track refresh duration by query and compare source-row volumes.

Although Parse or cast the field to the intended scalar type and validate malformed values fits the separate issue that a numeric string fails a greater-than predicate intended for an integer field because type-aware KQL comparisons cannot reliably treat arbitrary strings as measured numbers, this case concerns a query uses the wrong database context for a reference table and should be resolved with Qualify or select the correct KQL database and verify table access.

Option Investigate datetime parsing failures and quarantine bad source records would focus on the separate issue that events with invalid timestamps are silently excluded from an hourly report because invalid event-time values should not be treated as zero observations, not the current requirement that a query uses the wrong database context for a reference table; the appropriate remedy is Qualify or select the correct KQL database and verify table access.

Choosing Use a text sort on raw timestamps with mixed formats as proof of true event ordering would not satisfy the case condition (a query uses the wrong database context for a reference table), because typed event chronology needs explicit parsing and normalization; Qualify or select the correct KQL database and verify table access preserves the intended result.

The option Remove unneeded global sorting or restructure the calculation applies to the separate issue that a global ORDER BY is unnecessary for a downstream aggregation but dominates the plan, because global ordering can introduce single-node or non-scalable operations in MPP execution; the current condition is a join multiplies rows and then requires a large unnecessary DISTINCT, which calls for Fix source grain and join cardinality instead of masking the issue with DISTINCT.

Choosing Add ORDER BY to every intermediate query as a universal warehouse performance improvement would not satisfy the case condition (a join multiplies rows and then requires a large unnecessary DISTINCT), because sorting introduces work and is not automatically useful for distributed joins; Fix source grain and join cardinality instead of masking the issue with DISTINCT preserves the intended result.

The action Inspect query plan and relevant statistics for the filter and join columns solves a selective query scans far more rows than expected and the plan estimates are poor because accurate cardinality estimates help the optimizer choose efficient execution plans; it does not by itself solve a join multiplies rows and then requires a large unnecessary DISTINCT, whereas Fix source grain and join cardinality instead of masking the issue with DISTINCT does.