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| Section | Objectives |
|---|---|
| Preparing and Deploying Forcepoint DSPM | - DSPM Deployment Architecture - Data Source Configuration - Lab Environment Preparation - User Management Configuration |
| Analytics and Dashboards | - Analytic Dashboards - Risk Analysis and Reporting - Dashboard Customization - Enterprise Search |
| Compliance Hub and Data Register | - Security Posture Policies - Data Asset Inventory - Departments Configuration - Metadata Management |
| Data Discovery and Scanning | - Scan Configuration - SMB Data Sources - LDAP Integration - Data Visibility and Monitoring |
| Controls Orchestration | - Webhook Configuration - Rule Creation and Management - Risk Classification - Incident Investigation |
| Pattern Matching and Classification | - Classification Policies - Custom Pattern Creation - Sensitive Data Identification - Regular Expressions |
| Detector Configuration | - Regular Expression Detectors - Detector Testing and Validation - Path Detectors - Keyword Detectors |
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NEW QUESTION # 18
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: D
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 # 19
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 # 20
When Control Orchestration rules are triggered where can you find the events?
Answer: A
Explanation:
Triggered Controls Orchestration rule events are found under Incidents . In Forcepoint DSPM, Controls Orchestration rules are designed to identify data that requires attention by evaluating selected datasets, such as files, trustees, or agent activities, against rule conditions. When a rule condition is met, the result is operationalized as an incident so the security or governance team can review the matched data and determine the appropriate response.
Forcepoint's documentation states that each Controls Orchestration rule is "automatically added as a card in the Incidents tab," and selecting an incident card takes the administrator back to the related rule. It also explains that the Incidents section provides a top-down view of all orchestration rules and available match results. The documented navigation path is Policy Center > Incidents .
The other options are not the correct location for triggered orchestration events. Default dashboards and overviews provide summary visibility, but they are not the dedicated rule-event review workspace. Analytics supports broader investigation and reporting, but Controls Orchestration match results are reviewed through the Incidents workflow. References/topics: Policy Center, Controls Orchestration, Incidents, Rule Match Results, Enterprise Search Review .
NEW QUESTION # 21
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: D
NEW QUESTION # 22
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 # 23
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