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Notebook source can be shared and must not expose long-lived credentials. This addresses secure notebook data access; it does not directly satisfy conduct exploratory notebook-based security analysis.

Notebook results may contain confidential incident and identity evidence. Its intended use is to prevent notebook investigation data leaks, whereas this case requires the analyst to conduct exploratory notebook-based security analysis.

Notebook code can retain environment-specific workspace identifiers. That action focuses on correct a copied notebook workspace target rather than the specified need to conduct exploratory notebook-based security analysis.

Asynchronous KQL jobs are suited to broad historical multi-source correlations. Its intended use is to run a one-time long-range correlation, whereas this case requires the analyst to choose active detection for immediate threats.

Search jobs materialize relevant original records for one-table historical investigations. That action focuses on retrieve detailed historical records rather than the specified need to choose active detection for immediate threats.

Summary rules are designed for frequent aggregate materialization. This addresses sustain recurring short-interval metrics; it does not directly satisfy choose active detection for immediate threats.

Scheduled jobs can continue running until their schedule is explicitly retired. This addresses decommission outdated lake jobs; it does not directly satisfy right-size costly historical job schedules.

Stale promoted output can mask failed background query jobs. That action focuses on repair a failed scheduled lake enrichment rather than the specified need to right-size costly historical job schedules.

Jobs can materialize valid results in an unintended location if output bindings are wrong. This addresses prevent lake job results landing in a test table; it does not directly satisfy right-size costly historical job schedules.

Data minimization applies to precomputed security summaries as well as raw events. This addresses minimize sensitive summary output; it does not directly satisfy share stable SOC summary metrics.

Successfully aggregating an empty dataset does not prove telemetry health. Its intended use is to identify empty summaries caused by missing input, whereas this case requires the analyst to share stable SOC summary metrics.

Changes to rollup dimensions can alter the meaning of existing detections. This addresses protect dependent analytics from summary schema drift; it does not directly satisfy share stable SOC summary metrics.

Search jobs materialize relevant original records for one-table historical investigations. This addresses retrieve detailed historical records; it does not directly satisfy sustain recurring short-interval metrics.

Asynchronous KQL jobs are suited to broad historical multi-source correlations. Its intended use is to run a one-time long-range correlation, whereas this case requires the analyst to sustain recurring short-interval metrics.

Detection rules directly process eligible arriving events with lower latency. That action focuses on choose active detection for immediate threats rather than the specified need to sustain recurring short-interval metrics.

Search jobs target historical asynchronous investigations, not routine low-latency alerts. Its intended use is to distinguish search jobs from active analytic rules, whereas this case requires the analyst to execute complex multi-table historical correlation.

Search jobs can query applicable historical archived records outside later lake onboarding coverage. That action focuses on access pre-onboarding archived events rather than the specified need to execute complex multi-table historical correlation.

Search jobs can return large single-table result sets into a queryable investigation table. This addresses materialize one-table forensic search results; it does not directly satisfy execute complex multi-table historical correlation.

KQL jobs can correlate supported data lake records with rich KQL operators. This addresses query recent lake records across tables; it does not directly satisfy retrieve pre-onboarding legacy archive evidence.

Multi-table historical query coverage is constrained by available data in each source. That action focuses on establish exact historical search completeness rather than the specified need to retrieve pre-onboarding legacy archive evidence.

Interactive hot queries are a better fit for immediate small-horizon analysis. This addresses avoid unnecessary historical computation; it does not directly satisfy retrieve pre-onboarding legacy archive evidence.

Job creation paths differ by job type and are not interchangeable. This addresses schedule notebooks through the correct interface; it does not directly satisfy connect scheduled notebook output to reporting.

Notebook jobs can execute approved notebooks on a schedule where supported. Its intended use is to automate recurring notebook analysis, whereas this case requires the analyst to connect scheduled notebook output to reporting.

Notebook execution depends on compatible runtime libraries and environment state. This addresses restore notebook job dependencies; it does not directly satisfy connect scheduled notebook output to reporting.

Summary tables typically discard low-level fields not included in the aggregation. This addresses retain per-connection forensic detail; it does not directly satisfy produce hourly host flow summaries.

Derived summary tables make selected low-cost-tier information available for active analysis. Its intended use is to build hot detection signals from verbose logs, whereas this case requires the analyst to produce hourly host flow summaries.

Summary rules depend on valid input schema and successful scheduled runs. That action focuses on restore broken summary rule output rather than the specified need to produce hourly host flow summaries.

KQL lake coverage does not retroactively include all prior historical archive data. Its intended use is to retrieve pre-onboarding legacy archive evidence, whereas this case requires the analyst to query recent lake records across tables.

Multi-table historical query coverage is constrained by available data in each source. That action focuses on establish exact historical search completeness rather than the specified need to query recent lake records across tables.

Interactive hot queries are a better fit for immediate small-horizon analysis. This addresses avoid unnecessary historical computation; it does not directly satisfy query recent lake records across tables.

Tool integrations must respect the authorization of underlying security data. This addresses prevent MCP-based privilege escalation; it does not directly satisfy connect a notebook to Sentinel MCP tools.

Tool destination trust boundaries matter for confidential incident data. That action focuses on protect sensitive data in MCP integrations rather than the specified need to connect a notebook to Sentinel MCP tools.

AI-assisted tool summaries are not substitutes for raw event provenance. This addresses ground MCP-assisted threat findings in source logs; it does not directly satisfy connect a notebook to Sentinel MCP tools.