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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Administration and Configuration | 20% | - Policy creation and enforcement - System settings and maintenance - User and role management - Controls orchestration |
| Topic 2: DSPM Architecture and Deployment | 20% | - Installation and configuration - Integration with cloud and on-prem environments - Deployment planning and requirements - Architecture overview and components |
| Topic 3: Troubleshooting and Maintenance | 10% | - Upgrade and patch management - System health monitoring - Log analysis and error resolution - Backup and recovery procedures |
| Topic 4: Data Discovery and Classification | 25% | - Scanner and detector configuration - Pattern matching and classification rules - Data register and sensitive data mapping - Compliance framework alignment |
| Topic 5: Monitoring, Analytics, and Reporting | 10% | - Dashboard creation and customization - Compliance reporting and audit logs - Alert configuration and monitoring - Analytics and data visualization |
| Topic 6: Access Governance and Risk Management | 15% | - Data access governance policies - Risk scoring and prioritization - Access review and entitlement analysis - Incident handling and remediation |
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NEW QUESTION # 35
Which of the following statements describe real-world application of pattern matching in Forcepoint DSPM?
Select two.
Answer: A,B
Explanation:
The correct answers are B and C . Forcepoint DSPM pattern matching is used to identify specific information inside documents during scans. Forcepoint defines pattern matching as functionality that identifies "particular pieces of information in a document" by using regular expressions that match file content. A credit-card-like numeric string is a direct fit because it represents structured sensitive data that can be detected using a predictable format and then associated with compliance obligations such as PCI-related handling.
Option C is also valid because Forcepoint DSPM supports custom identification of sensitive business data, including intellectual property and trade secrets. A regular expression can be configured to detect proprietary product identifiers, engineering codes, project names, or other technical markers associated with confidential product development. Forcepoint's pattern terminology defines a Pattern as the RegEx plus the rules associated with detection, and allows classification, compliance, and distribution tags to be applied when the pattern is detected.
Options A , D , and E describe general regex use cases outside Forcepoint DSPM pattern matching. They focus on scripting, log parsing, and web-form validation rather than data discovery, classification, and governance. References/topics: Pattern Matching, RegEx, Classification Tags, Compliance Tags, Sensitive Data Discovery .
NEW QUESTION # 36
Which of the following is NOT a widget type available in Forcepoint DSPM dashboards?
Answer: C
Explanation:
The correct answer is B. Heatmap . Forcepoint DSPM dashboards are built from configurable widgets that present scan, access, classification, and risk data in different visual formats. The official Forcepoint DSPM widget list includes Counter , Chart , Map , Text , Table , Incidents , Dual Data Grouping , and Multi Counter . Heatmap is not listed as an available dashboard widget type.
The other answer choices are valid widget types. Counter widgets provide quick numerical summaries, such as counts of sensitive files, risky users, or matching records from selected datasets. Forcepoint describes Counter widgets as useful for at-a-glance metrics and supports aggregation functions such as count, sum, average, min, max, and median. Chart widgets visualize grouped data using supported chart formats, including horizontal bar, vertical bar, line, area, or pie charts. Text widgets are also part of the documented widget list and are used for static explanatory or contextual information on a board.
Therefore, Heatmap is the non-valid option. References/topics: Analytics, Dashboards, Widgets, Counter, Chart, Text, Dashboard Components .
NEW QUESTION # 37
When creating a Detector, which field allows you to exclude specific criteria from the search?
Answer: C
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 # 38
What is the purpose of assigning compliance tags to data patterns in Forcepoint DSPM?
Answer: C
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 # 39
Match the type of detector with its primary function.
Answer:
Explanation:
Explanation:
Path Detectors = Monitor storage locations of sensitive data
Content Detectors = Analyze data within files for sensitive data
Attribute Detectors = Identify meta-data within documents
Forcepoint DSPM separates detector logic into path, content, and attribute-based functions so classification can be driven by where data is stored, what the file contains, and what scan-derived attributes describe the file. Path Detectors evaluate file path information, including directory location, filename, and extension.
Forcepoint describes them as identifying and classifying files based on directory location and file extensions, which aligns with monitoring storage locations where sensitive data resides.
Content Detectors inspect the actual contents of files. Forcepoint states that content detectors analyze file content and categorize based on keywords, phrases, positive and negative terms, or patterns, making them the correct match for analyzing data within files for sensitive data.
Attribute Detectors operate on scan-result attributes rather than raw text content alone. Forcepoint describes them as defining criteria for "critical" and "sensitive" based on attributes in scan results, including ML output or path/content detector hits. This maps most closely to identifying metadata or scan-derived characteristics within documents. References/topics: Detectors, Path Detectors, Content Detectors, Attribute Detectors, AI Mesh, Classification Model .
NEW QUESTION # 40
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