Pass Your Microsoft AB-900 Exam Easy!

DLP incidents show sensitive data matches and policy enforcement. Its purpose is investigation of sensitive document transfer; the specified need is review of harmful employee messages.

Insider-risk evidence combines configured user-activity risk signals. It would support insider-driven exfiltration case, not the stated review of harmful employee messages.

eDiscovery organizes litigation-related content finding and holding. Its purpose is formal legal evidence collection; the specified need is review of harmful employee messages.

Content policy and data-loss alerts address different violation classes. The action is relevant to AI-related communication policy triage rather than assessment of AI-relevant compliance duties.

AI-specific signals can surface use of protected data categories. The action is relevant to classified information used during AI interactions rather than assessment of AI-relevant compliance duties.

eDiscovery can retrieve supported recorded AI interactions for cases. This helps with legally responsive Copilot conversations instead of the required assessment of AI-relevant compliance duties.

Communication Compliance is designed for supported conduct and policy review of messages. That addresses problematic workplace messages, whereas the current case requires locating sensitive identity data.

Compliance Manager organizes compliance-control assessments and improvement tasks. It is used for framework evidence and control tracking; this scenario calls for locating sensitive identity data.

Insider risk focuses on configured risky behavior by trusted users. It is used for suspected malicious insider activity; this scenario calls for locating sensitive identity data.

Compliance Manager tracks completion and corresponding assessment status. Its purpose is regulatory readiness progress; the specified need is responsibility partition for assessed controls.

Assessment templates map controls to a selected framework. It would support regulation-specific control assessment, not the stated responsibility partition for assessed controls.

Improvement actions can track implementation evidence for assessment controls. Its purpose is documented proof of a compliance control; the specified need is responsibility partition for assessed controls.

AI posture telemetry identifies sensitive-data use in AI applications. The action is relevant to sensitive information in AI prompts rather than activity behind an actual label downgrade.

eDiscovery search selects responsive content for a case. This helps with litigation-driven content collection instead of the required activity behind an actual label downgrade.

Data classification inventory identifies matching content in covered workloads. The action is relevant to discovery of stored sensitive content rather than activity behind an actual label downgrade.

Insider risk correlates configured risky user actions. It is used for suspected departing-employee exfiltration; this scenario calls for privacy-protecting investigation.

Policy tuning reduces known benign matches without disabling relevant risk detection. It is used for fewer false-positive user-risk cases; this scenario calls for privacy-protecting investigation.

Case closure records the disposition and investigator rationale. That addresses auditable disposition of employee-risk alert, whereas the current case requires privacy-protecting investigation.

DLP monitoring supports accountable follow-up on repeated violations. It would support repeated data-loss incident response, not the stated impact testing of a new DLP rule.

Alert details identify the sensitive type, location and enforcement reason. Its purpose is evidence for a sensitive outbound email block; the specified need is impact testing of a new DLP rule.

Governed exceptions avoid weakening protection for all users. Its purpose is narrowly authorized protected-data sharing; the specified need is impact testing of a new DLP rule.

Review dispositions preserve a decision trail for policy violations. The action is relevant to accountable escalation of flagged messages rather than tuned employee communication policy.

Role-controlled review limits access to sensitive conversation content. This helps with protected access to communications investigations instead of the required tuned employee communication policy.

Communication Compliance surfaces supported risky messages to authorized reviewers. The action is relevant to conduct-related Teams message review rather than tuned employee communication policy.

Data access governance focuses site access exposure rather than classification actions. It is used for sites creating broad sharing links; this scenario calls for Copilot DLP trigger timeline.

Case-based discovery locates responsive items and preserves review controls. That addresses formal litigation content collection, whereas the current case requires Copilot DLP trigger timeline.

Activity explorer records content classification actions over time. It is used for temporal label-usage evidence; this scenario calls for Copilot DLP trigger timeline.

AI posture management surfaces supported app usage and sensitive-data risk patterns. Its purpose is unsanctioned AI exposure insight; the specified need is prioritized sensitive prompt exposure response.

DLP provides enforcement evidence for supported AI content flows. Its purpose is AI-specific data loss prevention; the specified need is prioritized sensitive prompt exposure response.

Activity detail offers contextual evidence subject to permission and capture rules. It would support specific risky AI interaction evidence, not the stated prioritized sensitive prompt exposure response.

Case segregation controls evidence scope and reviewer authority. This helps with distinct legal matter boundaries instead of the required litigation preservation before review.

eDiscovery identifies responsive records using case search conditions. The action is relevant to targeted email discovery rather than litigation preservation before review.

AI interactions can be subject to discovery using supported item types. The action is relevant to litigation search across AI conversations rather than litigation preservation before review.