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| Section | Weight | Objectives |
|---|---|---|
| DSPM Architecture and Deployment | 20% | - Architecture overview and components - Integration with cloud and on-prem environments - Installation and configuration - Deployment planning and requirements |
| Monitoring, Analytics, and Reporting | 10% | - Analytics and data visualization - Dashboard creation and customization - Alert configuration and monitoring - Compliance reporting and audit logs |
| Troubleshooting and Maintenance | 10% | - System health monitoring - Upgrade and patch management - Log analysis and error resolution - Backup and recovery procedures |
| Administration and Configuration | 20% | - Policy creation and enforcement - User and role management - Controls orchestration - System settings and maintenance |
| Access Governance and Risk Management | 15% | - Risk scoring and prioritization - Access review and entitlement analysis - Incident handling and remediation - Data access governance policies |
| Data Discovery and Classification | 25% | - Pattern matching and classification rules - Scanner and detector configuration - Compliance framework alignment - Data register and sensitive data mapping |
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NEW QUESTION # 31
Which of the following are steps in creating a data classification and handling policy? Select four.
Answer: A,B,D,E
Explanation:
The correct selections are A, C, D, and E . A data classification and handling policy is a governance artifact that defines how data assets are categorized, owned, protected, reviewed, and aligned to legal or regulatory requirements. In Forcepoint DSPM, this sits within Policy Center and Compliance Hub , which are designed to support data classification, policy creation, security-control implementation, compliance, and risk reduction. Forcepoint states that Policy Center streamlines policy creation and prompts organizational representatives to provide information needed to build a governance framework aligned to organizational goals.
Specifying asset requirements maps to Data Mapping, where organizations define Data Asset Inventory fields and metadata such as retention period, business owner, regulatory scope, review status, and project name. Incorporating industry-specific regulations is required because departmental policy design must reflect obligations such as GDPR, HIPAA, and PCI DSS. Defining classification levels aligns to Taxonomy, where sensitivity levels such as Confidential, General Business, Public, and Highly Confidential are configured. Outlining roles and responsibilities aligns to assigning policy owners, department heads, representatives, and accountable stakeholders. Network traffic protocols are not a core step in creating a data classification and handling policy; they belong to network architecture or transport-control design, not data governance policy creation.
NEW QUESTION # 32
Isla wants to create a customized dashboard for the Finance department. Put the following steps in the correct order:
Answer:
Explanation:
Explanation:
4 # 2 # 6 # 5 # 3 # 1
The correct sequence begins with Create new board because a customized dashboard must first be instantiated before any department-specific design or filtering can be applied. Forcepoint's custom dashboard workflow starts in Analytics , where the administrator clicks +NEW BOARD . In the creation dialog, the administrator enters the dashboard Name , Group , and Description , then selects a template and chooses the dashboard layout. This maps directly to steps 4, 2, and 6 .
After the board exists, Isla can structure the dashboard. Forcepoint explains that dashboards are primarily built from panels and widgets : a panel is the organizational container, while widgets display information from selected datasets such as files, trustees, connectors, agents, database objects, or activities. Therefore, panels should be added before widgets so the dashboard has a clean layout framework for Finance-specific metrics.
The final step is applying filters using search strings or filter logic so the dashboard shows only Finance- relevant data. Filters constrain what the dashboard or widget displays, allowing the same analytics framework to focus on a specific department, dataset, risk type, classification, or data source. References/topics:
Analytics, Creating Custom Dashboards, Panels, Widgets, Dashboard Filters, GQL/Search Filtering .
NEW QUESTION # 33
Which of the following is NOT a key use case for detectors in Forcepoint DSPM?
Answer: B
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 # 34
Which statement best describes what happens when a detector group is selected while creating a content detector?
Answer: A
Explanation:
The correct answer is B . In Forcepoint DSPM, content detectors analyze file contents using configured search logic such as keywords, phrases, positive and negative terms, or regular expressions. During detector creation, administrators can associate the detector with a detector group. Forcepoint states that when a detector group is selected, the detector becomes part of the AI Mesh and contributes to classification results. If the administrator does not want the detector to influence classification, a non-AI Mesh detector group should be selected instead.
This is important because detector grouping controls whether detector hits are merely informational or actively influence classification decisions. A payroll detector, for example, may search for terms such as salary, payslip, compensation, or payroll. If tied into the AI Mesh, those hits can help classify files as sensitive or confidential. The other options misrepresent detector behavior. Detectors do not automatically revoke permissions, convert keywords directly into taxonomy labels, or disappear from scan results when grouped. References/topics: Administration > Detectors, Content Detectors, Detector Groups, AI Mesh, Classification Results, Contain/Not Contain Logic .
NEW QUESTION # 35
Why is it important to assign a data owner in each department in Forcepoint DSPM?
Answer: A
Explanation:
Assigning a data owner is important because Forcepoint DSPM treats ownership as a governance and accountability control. The correct answer is C : it ensures clear accountability and responsibility for data management. Data owners are the business stakeholders responsible for understanding the purpose, sensitivity, approved location, access model, and required protections for departmental data assets. Without an assigned owner, security teams may discover risk but lack the business context needed to validate whether exposure, access, retention, or classification is appropriate.
Forcepoint's DSPM release documentation describes Data Ownership as assigning clear ownership to each data asset to ensure accountability and foster responsibility. It also explains that once policies and controls are defined, DSPM can monitor for policy violations and alert the right data owner. This shows why ownership is central to operational response: findings are not just technical alerts; they are routed to accountable stakeholders who can approve, remediate, or explain the data condition.
The other options are incorrect. Data ownership does not restrict file creation by contributors, directly tune detector precision, or independently reduce false positives. Those outcomes depend on access controls, detector configuration, classification logic, and policy tuning. References/topics: Compliance Hub, Departments, Data Asset Inventory, Data Ownership, Controls Orchestration, Policy Violation Response .
NEW QUESTION # 36
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