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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Discovery and Classification | 25% | - Data register and sensitive data mapping - Pattern matching and classification rules - Compliance framework alignment - Scanner and detector configuration |
| Topic 2: Administration and Configuration | 20% | - Controls orchestration - System settings and maintenance - User and role management - Policy creation and enforcement |
| Topic 3: Troubleshooting and Maintenance | 10% | - Backup and recovery procedures - System health monitoring - Log analysis and error resolution - Upgrade and patch management |
| Topic 4: Monitoring, Analytics, and Reporting | 10% | - Compliance reporting and audit logs - Analytics and data visualization - Alert configuration and monitoring - Dashboard creation and customization |
| Topic 5: DSPM Architecture and Deployment | 20% | - Deployment planning and requirements - Integration with cloud and on-prem environments - Architecture overview and components - Installation and configuration |
| Topic 6: Access Governance and Risk Management | 15% | - Incident handling and remediation - Risk scoring and prioritization - Access review and entitlement analysis - Data access governance policies |
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NEW QUESTION # 10
The Forcepoint DSPM dashboards can simplify which of the following tasks? Select three.
Answer: A,D,E
Explanation:
The correct selections are Identifying high-risk users , Identifying ROT data , and Identifying critical data assets . Forcepoint DSPM Analytics includes pre-defined dashboards, or boards, that summarize scan findings into operational views for security, compliance, and data-governance teams. Forcepoint states that Analytics boards present scan-derived metrics such as overexposed files, sensitive data, and data at risk, helping teams make informed decisions about vulnerabilities, risks, and compliance issues.
The pre-defined board list directly supports the three correct options. High Risk Users identifies users with excessive permissions or abnormal access patterns, supporting insider-threat reduction and least-privilege enforcement. ROT Data identifies redundant, obsolete, or trivial data so teams can reduce clutter, unnecessary exposure, and policy risk. Key Data Overview highlights critical data assets, allowing teams to prioritize protection of the organization's most valuable and sensitive information.
The other answers are not the best matches for dashboard simplification in this question. Database assets are handled through structured-data discovery and database-specific workflows, not the named dashboard use cases here. User credentials may be detected as sensitive content in scans, but identifying credentials is not listed as a primary pre-defined dashboard task. References/topics: Analytics, Pre-defined Boards, Data Classification, Data Hygiene, Data Risk, High Risk Users, ROT Data, Key Data Overview .
NEW QUESTION # 11
Which of the following utilizes artificial intelligence and machine learning when data is scanned?
Answer: C
Explanation:
The correct answer is D. Detectors . In Forcepoint DSPM, detectors are scan-time classification components that can contribute to the broader AI Mesh , now represented in the UI as the Classification Model .
Forcepoint describes the Classification Model as the mechanism that combines detection signals from keyword lists, regex patterns, machine-learning models, and topic classifiers into a pipeline that assigns classification tags such as Confidential , Internal , or Public . It also identifies Detector Groups as nodes that assess file paths and file contents using rule-based logic, including regular expressions and keywords.
This makes detectors the best answer among the listed options because they operate during scanning and feed classification outcomes. Forcepoint's detector documentation states that content detectors analyze file content to detect and categorize documents, and further notes that when a detector group is selected, the detector becomes part of the AI Mesh and contributes to classification results.
The other choices are not the primary AI/ML scan-time component. Patterns are regular-expression rules.
Data mapping defines Data Asset Inventory metadata fields. Compliance Hub manages governance policy artifacts, policy acceptance, reviews, and audit trail functions. References/topics: Detectors, AI Mesh, Classification Model, Content Detectors, Scan Classification Pipeline .
NEW QUESTION # 12
What is the purpose of assigning compliance tags to data patterns in Forcepoint DSPM?
Answer: D
Explanation:
Compliance tags in Forcepoint DSPM are used to associate detected data patterns with regulatory or compliance obligations. The correct answer is B because these tags help the platform identify files and data objects that may fall under privacy, security, or industry-specific regulatory regimes. Forcepoint's pattern- matching terminology defines Compliance as tags that help organizations conform to regulatory regimes, and gives the example of applying tags such as GDPR/PII to a Social Security number pattern so related documents can be identified.
Operationally, this means a pattern is not only detecting a technical string, such as a national identifier, payment card number, or health-related value; it is also attaching compliance meaning to the match. That compliance context can then support classification, filtering, analytics, remediation prioritisation, and audit evidence. Forcepoint also states that when adding a new pattern, selected Classification, Compliance, and Distribution values can override machine-learning model output during scans, making the assigned tags authoritative for scan results.
The other options are adjacent but incorrect. User monitoring and reporting are downstream analytics activities, encryption policy management is not the core purpose of pattern compliance tagging, and user credentials are handled through identity and access management workflows. References/topics: Pattern Matching, Compliance Tags, Classification Model, AI Mesh, Regulatory Data Identification .
NEW QUESTION # 13
When creating a Detector, which field allows you to exclude specific criteria from the search?
Answer: B
Explanation:
The correct answer is A. Not contain . In Forcepoint DSPM, detector creation uses inclusion and exclusion logic to control what should trigger a detector match. The Contain field defines the positive match criteria:
the keywords, phrases, regular expressions, extensions, or path terms that the detector should search for. The Not Contain field provides the negative condition: terms or criteria that should be ignored even when the broader detector logic would otherwise match.
Forcepoint's DSPM documentation for Content Detectors states that if there are terms the detector should ignore, they are set in the Not Contain field. The same concept appears in Path Detectors , where administrators define the search method, populate Contain with triggering terms, and then use Not Contain to exclude terms from matching.
This matters operationally because detectors can otherwise generate excessive or misleading matches. For example, a detector looking for payroll-related content may include "salary" or "compensation" in Contain , while excluding harmless template, archive, or test terms in Not Contain . Not Add , Except , and Exclude are not the documented detector-configuration field names. References/topics: Administration > Detectors, Content Detectors, Path Detectors, Contain/Not Contain logic, AI Mesh detector contribution .
NEW QUESTION # 14
What is the primary function of a detector in Forcepoint DSPM?
Answer: C
Explanation:
A detector in Forcepoint DSPM is a rule-based classification component used during scanning to identify files whose content or path matches defined detection logic. The correct answer is B because detectors are designed to locate specific patterns, words, or expressions and then contribute to classification/tagging outcomes. Forcepoint describes Detector Groups in AI Mesh as components where "detectors assess both the file path and its contents using rule-based logic, such as regular expressions and keywords," returning a match when the content fits the defined patterns.
This is distinct from AI classifiers, which infer sensitive-data meaning from broader semantic or machine- learning signals. Detectors are the more deterministic mechanism: they look for defined indicators such as a keyword, phrase, regular expression, or path element. Forcepoint release notes also describe detector functionality as allowing content or path search when creating a detector, including an example where adding the word Archive to a detector can tag files located in an Archive folder.
The other options confuse detectors with unrelated platform functions. Detectors do not create credential tags specifically, optimize network throughput, block files for speed, or increase storage capacity. References
/topics: Detectors, Pattern Matching, AI Mesh, Classification Tags, Content and Path Search .
NEW QUESTION # 15
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