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| Section | Objectives |
|---|---|
| Topic 1: Compliance Hub and Data Register | - Departments Configuration - Security Posture Policies - Metadata Management - Data Asset Inventory |
| Topic 2: Analytics and Dashboards | - Analytic Dashboards - Enterprise Search - Risk Analysis and Reporting - Dashboard Customization |
| Topic 3: Controls Orchestration | - Incident Investigation - Rule Creation and Management - Webhook Configuration - Risk Classification |
| Topic 4: Pattern Matching and Classification | - Regular Expressions - Custom Pattern Creation - Sensitive Data Identification - Classification Policies |
| Topic 5: Data Discovery and Scanning | - LDAP Integration - Data Visibility and Monitoring - SMB Data Sources - Scan Configuration |
| Topic 6: Detector Configuration | - Regular Expression Detectors - Path Detectors - Detector Testing and Validation - Keyword Detectors |
| Topic 7: Preparing and Deploying Forcepoint DSPM | - Lab Environment Preparation - User Management Configuration - DSPM Deployment Architecture - Data Source Configuration |
>> Lab DSPM-Deploy-and-Administer Questions <<
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NEW QUESTION # 14
What are the key organizational elements for creating a dashboard in Forcepoint DSPM? Select two.
Answer: C,E
Explanation:
The correct answers are Widgets and Panels . In Forcepoint DSPM Analytics, dashboards are organized as boards that present scan-derived security, compliance, and data-risk information. The primary structural components used to build those dashboards are panels and widgets. Forcepoint states that dashboards are
"primarily constructed of panels and widgets," and explains that each panel can contain one or more widgets.
A panel acts as the container that organizes multiple visual components into a coherent dashboard layout, while a widget is the smaller information component that displays data from selected datasets such as files, trustees, connectors, or agents.
This structure matters because dashboards are not just static reports; they are configurable analytical workspaces. Widgets provide the actual data presentation, such as counters, charts, maps, text blocks, tables, incidents, dual data grouping, or multi-counter views. Forcepoint separately lists these as available widget types, each with its own customization options. Panels then provide the organizational layer that groups these widgets logically by use case, such as exposure, classification, incident review, user risk, or compliance posture. Toggle switches, menus, and status bars may appear in the interface, but they are not the dashboard- building elements. References/topics: Analytics, Components of a Dashboard, Widgets, Panels, Custom Dashboards .
NEW QUESTION # 15
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 # 16
What is the first step in configuring the Data Register in Forcepoint DSPM?
Answer: C
Explanation:
The first step in configuring the Data Register is Creating Security Posture Policies . In Forcepoint DSPM, the Data Register is the governance workspace where an organization defines and manages its most important data assets, commonly described as "crown jewels." Forcepoint's Data Register structure lists three main areas in order: Security Posture Policies , Data Asset Inventory , and Review Status , making Security Posture Policies the starting point for register configuration.
A Security Posture Policy creates the formal representation of a governed data asset. The documented workflow is to navigate to Policy Center > Data Register > Security Posture Policies , click Add new Security Posture Policy , and define required details such as Asset Name , Department , Data Owner , and Data Mapping using a GQL query.
The other choices are not the first Data Register configuration step. Pattern Matching belongs to detection and classification logic, not Data Register setup. Data Mapping is important, but it is configured under Compliance Hub as the framework for Data Asset Inventory metadata fields. Reviewing policies in the Data Asset Inventory occurs after policies and asset definitions exist. References/topics: Policy Center, Data Register, Security Posture Policies, Data Asset Inventory, Data Mapping, Data Ownership .
NEW QUESTION # 17
What is the primary function of a detector in Forcepoint DSPM?
Answer: B
Explanation:
A detector in Forcepoint DSPM is a rule-based classification component used during scanning to identify files whose content or path matches defined detection logic. The correct answer is B because detectors are designed to locate specific patterns, words, or expressions and then contribute to classification/tagging outcomes. Forcepoint describes Detector Groups in AI Mesh as components where "detectors assess both the file path and its contents using rule-based logic, such as regular expressions and keywords," returning a match when the content fits the defined patterns.
This is distinct from AI classifiers, which infer sensitive-data meaning from broader semantic or machine- learning signals. Detectors are the more deterministic mechanism: they look for defined indicators such as a keyword, phrase, regular expression, or path element. Forcepoint release notes also describe detector functionality as allowing content or path search when creating a detector, including an example where adding the word Archive to a detector can tag files located in an Archive folder.
The other options confuse detectors with unrelated platform functions. Detectors do not create credential tags specifically, optimize network throughput, block files for speed, or increase storage capacity. References
/topics: Detectors, Pattern Matching, AI Mesh, Classification Tags, Content and Path Search .
NEW QUESTION # 18
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 # 19
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