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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Maintenance | 10% | - Upgrade and patch management - Log analysis and error resolution - Backup and recovery procedures - System health monitoring |
| Topic 2: Monitoring, Analytics, and Reporting | 10% | - Analytics and data visualization - Alert configuration and monitoring - Compliance reporting and audit logs - Dashboard creation and customization |
| Topic 3: Administration and Configuration | 20% | - User and role management - Controls orchestration - Policy creation and enforcement - System settings and maintenance |
| Topic 4: DSPM Architecture and Deployment | 20% | - Installation and configuration - Integration with cloud and on-prem environments - Deployment planning and requirements - Architecture overview and components |
| Topic 5: Data Discovery and Classification | 25% | - Pattern matching and classification rules - Compliance framework alignment - Scanner and detector configuration - Data register and sensitive data mapping |
| Topic 6: Access Governance and Risk Management | 15% | - Access review and entitlement analysis - Incident handling and remediation - Data access governance policies - Risk scoring and prioritization |
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NEW QUESTION # 35
The Forcepoint DSPM dashboards can simplify which of the following tasks? Select three.
Answer: B,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 # 36
Which of these is NOT a valid benefit of configuring Data Mapping in Forcepoint DSPM?
Answer: C
Explanation:
The correct answer is A. Resolves Incident Reporting . Data Mapping in Forcepoint DSPM is a governance configuration capability within Policy Center > Compliance Hub , not an incident-resolution mechanism.
Forcepoint defines Data Mapping, also referred to as Security Posture Policy Controls , as the building blocks for the Data Asset Inventory framework. It allows administrators to define the fields available in the Data Asset Inventory so data owners can assign metadata tags to critical data. Examples include retention period, business owner, regulatory scope, review status, and project name .
Those functions clearly support the valid benefits in the option set. Data Mapping improves data management by standardizing asset metadata. It enhances compliance by capturing regulatory scope and review-related fields. It also streamlines internal processes by giving departments a consistent structure for documenting ownership, retention, review status, and business context. Forcepoint also notes that only one data mapping configuration is available, so it should be designed generically enough for all departments, reinforcing its role as an enterprise-wide governance framework.
Incident reporting is handled separately through DSPM incident and controls-orchestration workflows. Data Mapping may enrich incident context, but it does not "resolve" incident reporting. References/topics:
Compliance Hub, Data Mapping, Security Posture Policy Controls, Data Asset Inventory, Metadata Governance .
NEW QUESTION # 37
Which of the following statements is true about Forcepoint DSPM pattern matching?
Answer: C
Explanation:
The correct answer is A . Forcepoint DSPM pattern matching is designed to let administrators define and tune custom detection logic for organisation-specific sensitive data. The documented pattern-matching function identifies particular information in documents by using Regular Expressions , and Forcepoint notes that pattern matching uses Golang RegEx syntax, which is separate from Detector syntax.
When a new pattern is added under Administration > Pattern Matching , the configuration includes Pattern Name , Regular Expression , enablement state, hidden RegEx handling, and tag assignments for Classification , Compliance , and Distribution . Forcepoint states that the Regular Expression is "the sequence to be matched," and that selected tags can override machine-learning model output during endpoint suggestions and file scans. This supports the principle that custom patterns can be adjusted so the RegEx better matches an organisation's data formats, identifiers, project codes, or regulatory artifacts.
The other statements do not match the documented pattern workflow. Country assignment is not presented as a core custom-pattern field. Export/import of data patterns is not part of the stated pattern-matching configuration flow. Default or preconfigured patterns are provided as built-in detection content and should not be treated as administrator-editable RegEx templates. References/topics: Pattern Matching, Add New Pattern, RegEx, Classification Tags, Compliance Tags, Distribution Tags .
NEW QUESTION # 38
Anna created a complex GQL query that she plans on using weekly to filter the results and export the data for review. How can she store this query for repeated use?
Answer: B
Explanation:
The correct answer is C . Forcepoint DSPM allows frequently used Enterprise Search filters to be saved as bookmarks, which is the appropriate method for Anna's weekly workflow. The documented Enterprise Search capability states that the page lets users access recently used filters, save frequently used filters as bookmarks, customize column headings, and generate meaningful reports. It also supports advanced filtering through GetVisibility Query Language , where a GQL query narrows scanned-file results to a focused, manageable subset for analysis and action.
Operationally, Anna would go to Enterprise Search , enter the complex GQL filter in the search/query field, execute or validate the filter, and then select the star icon to bookmark it. Forcepoint support documentation confirms that administrators can save complex GQL queries by using the star icon, creating a GQL bookmark, and providing an appropriate description.
The other options are incorrect because DSPM does not use an Excel import workflow to load reusable GQL filters from Analytics or Enterprise Search. Administration is also not the documented location for saving Enterprise Search GQL bookmarks. References/topics: Enterprise Search, GQL Filtering, Bookmarked Filters, Exporting Data, Reusable Search Workflows .
NEW QUESTION # 39
Which of the following statements describe real-world application of pattern matching in Forcepoint DSPM?
Select two.
Answer: B,E
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 # 40
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