DSPM- Deploy-and-Administer Exam Dumps - Forcepoint DSPM Questions and Answers

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 .

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 .

The correct answers are B and C . Forcepoint DSPM pattern matching is used to identify specific information inside documents during scans. Forcepoint defines pattern matching as functionality that identifies “particular pieces of information in a document” by using regular expressions that match file content. A credit-card-like numeric string is a direct fit because it represents structured sensitive data that can be detected using a predictable format and then associated with compliance obligations such as PCI-related handling.

Option C is also valid because Forcepoint DSPM supports custom identification of sensitive business data, including intellectual property and trade secrets. A regular expression can be configured to detect proprietary product identifiers, engineering codes, project names, or other technical markers associated with confidential product development. Forcepoint’s pattern terminology defines a Pattern as the RegEx plus the rules associated with detection, and allows classification, compliance, and distribution tags to be applied when the pattern is detected.

Options A , D , and E describe general regex use cases outside Forcepoint DSPM pattern matching. They focus on scripting, log parsing, and web-form validation rather than data discovery, classification, and governance. References/topics: Pattern Matching, RegEx, Classification Tags, Compliance Tags, Sensitive Data Discovery .

Administration > Taxonomy

Taxonomy tags are managed from the Administration menu, specifically under Administration > Taxonomy . In the screenshot, Adam should not select Policy Center ; the currently open menu shows Compliance Hub, Data Register, Controls Orchestration, and Incidents, but taxonomy management is not located there. The correct UI action is to open the Administration drop-down on the top navigation bar and select Taxonomy .

Forcepoint’s DSPM documentation states that the Taxonomy page displays predefined AI Mesh tags, which cannot be removed, and also allows administrators to add custom tags for pattern matching and detection rules. It further explains that taxonomy mapping can connect AI Mesh tags with data-source taxonomies so mapped tags can be written back as the organization’s own labels.

This location is important because taxonomy governs the classification language DSPM applies to scanned data. By updating taxonomy tags, Adam aligns DSPM classification output with the company’s internal handling policies, sensitivity labels, and compliance terminology. Forcepoint also notes that new taxonomy tags are created from the Taxonomy tab under the Administration section, and that applied tags are visible in the Data Asset Inventory. References/topics: Administration, Taxonomy, AI Mesh Tags, Classification Tags, Pattern Matching, Detection Rules .

The correct answer is D. Head of Department . In Forcepoint DSPM Compliance Hub, Departments represent organisational business units such as HR, Finance, or Payment Processing. They are used to mirror the company’s functional structure inside the governance workflow so that policies, data assets, ownership responsibilities, and review activities can be aligned to the correct business stakeholders. Forcepoint states that Departments are configured by defining company departments and assigning department representatives, with department heads or business-unit representatives acting as primary points of contact.

The documented workflow for adding a department is explicit: click Add new department , then enter the Department name , Head of Department , and Notify At email address, then save. This makes Head of Department the required field among the options listed. The field is important because department heads receive governance-related notifications and, when they log in, see only the Security Posture Policies and Data Asset Inventory assigned to their department.

The distractors belong to other workflows. Chief Reviewer is not the department-creation field. Group Name relates to user or group administration, not Compliance Hub department definition. GQL data mapping is used for identifying data assets within DSPM policy/data-mapping logic, not for creating a department. References/topics: Compliance Hub, Departments, Department Representatives, Policy Center, Data Asset Inventory visibility .

Workflow Configuration Tool → Allows the creation of GQL syntax rules with conditions for organizational files and users.

Rule-Based Automation → Establish criteria to identify data policy violations, data handling irregularities, and other anomalies.

Notification System → Triggered rules can be configured to generate alerts and send them to webhooks to ensure prompt action.

Incident Management → Review events and manage rules through cards.

Controls Orchestration in Forcepoint DSPM is the policy automation layer used to convert data-risk criteria into reviewable operational events. The Workflow Configuration Tool is represented by the rule-building interface under Policy Center > Controls Orchestration , where administrators define datasets, ownership, rule conditions, and GQL logic for organizational files, trustees, or agent activities. Forcepoint states that rules are created to identify data matching specific criteria and are applied during scans of the selected dataset.

Rule-Based Automation describes the criteria-driven detection model. Administrators establish rules that identify policy violations, data-handling irregularities, or other anomalies that require attention. Notification System maps to the ability to configure triggered rules to send external notifications, including webhook-based alerts, when matching data is detected. Incident Management maps to the Incidents workflow: Forcepoint states that each rule is automatically added as a card in the Incidents tab, and selecting the card takes the user back to the associated rule. References/topics: Policy Center, Controls Orchestration, GQL Conditions, Notifications, Webhooks, Incidents .

The correct selections are Rule-Based Automation, Incident Management, Webhook Notification System, and Workflow Configuration Tool . Forcepoint DSPM Controls Orchestration is built around rules that identify data requiring attention and can trigger notifications or automated responses. The official documentation describes Controls Orchestration as providing “automated work flows, rule-based detection, timely notifications, and efficient incident management,” which directly maps to these four options.

Rule-Based Automation is represented by custom rules that evaluate datasets such as files, trustees, or agent activities using GQL conditions. Workflow Configuration Tool is reflected in the rule-building process under Policy Center > Controls Orchestration , where administrators create rules, define ownership, select the asset, configure conditions, and enable the rule.

Webhook Notification System is valid because orchestration rules can send notifications outside Forcepoint DSPM, and webhook functionality sends HTTP requests to a configured callback endpoint when a defined condition is met. Incident Management is also core because each rule is automatically added as a card in the Incidents tab, linking detected conditions to operational review and response. Rule-Based Remediation is not the best answer here because remediation is an outcome of automated response workflows, not the named key feature in this option set. References/topics: Controls Orchestration, GQL Rules, Webhooks, Incidents, Policy Center .

The correct answer is B . Forcepoint DSPM Controls Orchestration rules are built around query-driven rule logic. In the rule configuration workflow, administrators select a dataset such as Files , Trustees , or Agent Activities , then configure the rule condition using GQL syntax . This GQL condition defines which records match the rule and therefore which results appear as incidents when the rule is triggered. Forcepoint documentation states that Controls Orchestration rules identify data matching specific criteria and that the Condition field uses GQL syntax to filter the selected dataset.

When reviewing incidents, Forcepoint’s Incidents page provides a top-down view of orchestration rules and available match results. Selecting an incident card opens a results preview, and choosing View in the Page displays those matched files in Enterprise Search , where additional review and action options are available. Enterprise Search is specifically designed to narrow scanned-file results using GetVisibility Query Language , and Forcepoint notes that GQL filtering helps reduce the result set to a more manageable subset for analysis and action.

Timestamp, Risk type, and keyword filtering may be useful in other contexts, but the documented advanced review mechanism for these results is GQL-based filtering. References/topics: Controls Orchestration, Incidents, Enterprise Search, GQL Filtering, Rule Match Review .

Compliance tags in Forcepoint DSPM are used to associate detected data patterns with regulatory or compliance obligations. The correct answer is B because these tags help the platform identify files and data objects that may fall under privacy, security, or industry-specific regulatory regimes. Forcepoint’s pattern-matching terminology defines Compliance as tags that help organizations conform to regulatory regimes, and gives the example of applying tags such as GDPR/PII to a Social Security number pattern so related documents can be identified.

Operationally, this means a pattern is not only detecting a technical string, such as a national identifier, payment card number, or health-related value; it is also attaching compliance meaning to the match. That compliance context can then support classification, filtering, analytics, remediation prioritisation, and audit evidence. Forcepoint also states that when adding a new pattern, selected Classification, Compliance, and Distribution values can override machine-learning model output during scans, making the assigned tags authoritative for scan results.

The other options are adjacent but incorrect. User monitoring and reporting are downstream analytics activities, encryption policy management is not the core purpose of pattern compliance tagging, and user credentials are handled through identity and access management workflows. References/topics: Pattern Matching, Compliance Tags, Classification Model, AI Mesh, Regulatory Data Identification .

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.