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| Section | Objectives |
|---|---|
| Topic 1: Analytics and Dashboards | - Enterprise Search - Dashboard Customization - Analytic Dashboards - Risk Analysis and Reporting |
| Topic 2: Pattern Matching and Classification | - Custom Pattern Creation - Regular Expressions - Classification Policies - Sensitive Data Identification |
| Topic 3: Controls Orchestration | - Incident Investigation - Webhook Configuration - Rule Creation and Management - Risk Classification |
| Topic 4: Compliance Hub and Data Register | - Departments Configuration - Data Asset Inventory - Metadata Management - Security Posture Policies |
| Topic 5: Preparing and Deploying Forcepoint DSPM | - DSPM Deployment Architecture - Data Source Configuration - Lab Environment Preparation - User Management Configuration |
| Topic 6: Detector Configuration | - Detector Testing and Validation - Path Detectors - Regular Expression Detectors - Keyword Detectors |
| Topic 7: Data Discovery and Scanning | - LDAP Integration - SMB Data Sources - Scan Configuration - Data Visibility and Monitoring |
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NEW QUESTION # 16
Which of the following are steps in creating a data classification and handling policy? Select four.
Answer: A,B,C,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 # 17
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 # 18
Which of the following is a key benefit of defining a custom data taxonomy?
Answer: A
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 # 19
When creating a Security Posture Policy in Forcepoint DSPM, which field uses a GQL query to identify the data asset?
Answer: B
Explanation:
The correct answer is C. Data Mapping . In Forcepoint DSPM, Security Posture Policies are used to define and govern critical business data assets, often referred to as crown-jewel data. Each policy represents a managed data asset associated with a department, owner, and query-based definition. The Data Mapping field is where the administrator enters or edits the GQL query that identifies which files or records belong to that data asset. Forcepoint's documentation explicitly lists Asset Name , Department , Data Owner , and Data Mapping as required Security Posture Policy details, and defines Data Mapping as "a GQL query used to identify the data asset within the DSPM database." This distinction matters because Asset Name is only the business label, Department assigns responsibility to a business unit, and Data Owner identifies the person or group accountable for monitoring and compliance.
The actual technical selection logic is contained in Data Mapping , where GQL can match data across sources such as SMB and SharePoint using query criteria like source and path. References/topics: Policy Center, Data Register, Security Posture Policies, Data Mapping, GQL, Data Asset Inventory .
NEW QUESTION # 20
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 # 21
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