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| Section | Objectives |
|---|---|
| Topic 1: Data Discovery and Scanning | - Scan Configuration - SMB Data Sources - Data Visibility and Monitoring - LDAP Integration |
| Topic 2: Controls Orchestration | - Webhook Configuration - Incident Investigation - Risk Classification - Rule Creation and Management |
| Topic 3: Preparing and Deploying Forcepoint DSPM | - DSPM Deployment Architecture - Lab Environment Preparation - User Management Configuration - Data Source Configuration |
| Topic 4: Pattern Matching and Classification | - Classification Policies - Regular Expressions - Sensitive Data Identification - Custom Pattern Creation |
| Topic 5: Compliance Hub and Data Register | - Data Asset Inventory - Metadata Management - Security Posture Policies - Departments Configuration |
| Topic 6: Detector Configuration | - Regular Expression Detectors - Keyword Detectors - Detector Testing and Validation - Path Detectors |
| Topic 7: Analytics and Dashboards | - Dashboard Customization - Analytic Dashboards - Risk Analysis and Reporting - Enterprise Search |
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NEW QUESTION # 35
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 # 36
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 # 37
When Control Orchestration rules are triggered where can you find the events?
Answer: D
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 # 38
Why is it important to assign a data owner in each department in Forcepoint DSPM?
Answer: D
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 # 39
Which of the following is a key benefit of defining a custom data taxonomy?
Answer: C
Explanation:
The correct answer is D. Enhances data security . In Forcepoint DSPM, taxonomy is the structured classification model used to assign sensitivity meaning to discovered data. Forcepoint describes taxonomy as a machine-learning-based structured classification system that assigns sensitivity levels such as Confidential , General Business , Public , and Highly-Confidential . This classification directly corresponds to the Classification column in scan results, allowing security and governance teams to understand how sensitive a file or data asset is after scanning.
A custom taxonomy improves security because it lets an organisation align DSPM classification labels with its own internal data-handling rules, security protocols, and business language. Forcepoint notes that taxonomy customization ensures data handling aligns with an organisation's security protocols, and that applied tags are visible in the Data Asset Inventory . In the administration taxonomy workflow, Forcepoint also explains that predefined AI Mesh tags can be supplemented with custom tags for pattern matching and detection rules, and those tags can be mapped to data-source taxonomies for label writeback.
The other options describe possible operational goals but not the primary purpose of taxonomy. Taxonomy is not an authentication mechanism, deduplication feature, or storage-reduction tool. References/topics:
Taxonomy, Classification Tags, AI Mesh, Pattern Matching, Data Asset Inventory, Compliance Hub .
NEW QUESTION # 40
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