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| Section | Objectives |
|---|---|
| Detector Configuration | - Regular Expression Detectors - Keyword Detectors - Detector Testing and Validation - Path Detectors |
| Compliance Hub and Data Register | - Security Posture Policies - Departments Configuration - Data Asset Inventory - Metadata Management |
| Analytics and Dashboards | - Dashboard Customization - Enterprise Search - Risk Analysis and Reporting - Analytic Dashboards |
| Controls Orchestration | - Risk Classification - Incident Investigation - Webhook Configuration - Rule Creation and Management |
| Preparing and Deploying Forcepoint DSPM | - Data Source Configuration - User Management Configuration - Lab Environment Preparation - DSPM Deployment Architecture |
| Pattern Matching and Classification | - Classification Policies - Sensitive Data Identification - Regular Expressions - Custom Pattern Creation |
| Data Discovery and Scanning | - Data Visibility and Monitoring - SMB Data Sources - LDAP Integration - Scan Configuration |
>> DSPM-Deploy-and-Administer 100% Correct Answers <<
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NEW QUESTION # 11
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: C
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 # 12
Geoff is configuring the Data Asset Inventory. Which Security Posture Policy Control options are available for him to use? Select three.
Answer: B,C,D
Explanation:
The correct options are Yes/No, Select, and Text . In Forcepoint DSPM, Security Posture Policy Controls are configured under Policy Center > Compliance Hub > Data Mapping . These controls define the metadata fields that appear in the Data Asset Inventory , allowing data owners to describe and govern critical data assets using consistent business and compliance attributes. Forcepoint describes Data Mapping as the framework used to define 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.
The documented control types are Text , Yes/No , and Select . Text creates a free-form text field, useful for values such as project name or business context. Yes/No creates a binary drop-down, appropriate for simple governance questions such as whether a review is required. Select creates a predefined selection menu aligned with common data governance frameworks.
GQL query is not a Data Mapping control type; GQL is used elsewhere for search and Controls Orchestration rule conditions. Checkbox is also not listed as a supported Security Posture Policy Control option. References/topics: Compliance Hub, Data Mapping, Security Posture Policy Controls, Data Asset Inventory, Metadata Governance .
NEW QUESTION # 13
Which of the following statements is true about Forcepoint DSPM pattern matching?
Answer: A
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 # 14
Which of the following is NOT a key use case for detectors in Forcepoint DSPM?
Answer: A
Explanation:
The correct answer is A. Encrypting data transfers . Detectors in Forcepoint DSPM are classification and discovery components, not transport-security controls. A detector is used to analyze file content, file paths, attributes, keywords, phrases, regular expressions, and positive or negative match terms so the platform can identify and categorize data during scans. Forcepoint describes Content Detectors as tools that "analyze file content to detect and categorize" based on keywords, phrases, or patterns, making them directly relevant to finding sensitive information.
Detectors also support compliance and breach-prevention outcomes because their findings contribute to the broader DSPM visibility model: identifying where sensitive data exists, how it is classified, and where risk- reduction actions may be needed. Forcepoint describes DSPM as providing visibility and risk remediation across cloud and on-premises environments, and notes that AI technology combined with Detectors and Compliance Hub helps organizations protect sensitive information and maintain regulatory requirements.
Encryption of data transfers, however, is handled by transport protocols, connector configuration, network security controls, or platform security architecture-not by detector logic. Detectors can help discover sensitive data that may require protection, but they do not encrypt traffic. References/topics: Detectors, Content Detectors, AI Mesh, Sensitive Data Discovery, Compliance Hub, Risk Remediation .
NEW QUESTION # 15
Which of the following utilizes artificial intelligence and machine learning when data is scanned?
Answer: A
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 # 16
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