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| Section | Objectives |
|---|---|
| Detector Configuration | - Path Detectors - Regular Expression Detectors - Keyword Detectors - Detector Testing and Validation |
| Controls Orchestration | - Risk Classification - Webhook Configuration - Rule Creation and Management - Incident Investigation |
| Preparing and Deploying Forcepoint DSPM | - Lab Environment Preparation - DSPM Deployment Architecture - Data Source Configuration - User Management Configuration |
| Data Discovery and Scanning | - SMB Data Sources - LDAP Integration - Scan Configuration - Data Visibility and Monitoring |
| Compliance Hub and Data Register | - Data Asset Inventory - Security Posture Policies - Metadata Management - Departments Configuration |
| Pattern Matching and Classification | - Classification Policies - Regular Expressions - Sensitive Data Identification - Custom Pattern Creation |
| Analytics and Dashboards | - Risk Analysis and Reporting - Enterprise Search - Analytic Dashboards - Dashboard Customization |
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NEW QUESTION # 15
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 # 16
Put the following steps in order for applying a filter to a widget of a duplicated dashboard:
Answer:
Explanation:
Explanation:
1 # 3 # 4 # 2
The correct sequence is Select the Edit Widgets button , Open the Widget settings , Edit the GQL filter , and then Save the updated filter . In Forcepoint DSPM Analytics, a duplicated dashboard must first be placed into a widget-editable state before any individual widget configuration can be changed. Forcepoint describes dashboards as being built from panels and widgets , and identifies Edit Widgets as the control used to open the edit view for modifying widgets on a board. ( help.forcepoint.com ) After edit mode is active, the administrator opens the specific widget's settings because the filter is scoped to that widget rather than the whole dashboard. The GQL filter is then edited to constrain the widget's selected dataset, such as files, trustees, connectors, agents, database tables, or other analytics objects. This follows Forcepoint's dashboard model, where widgets present information from selected datasets and have their own customization options. ( help.forcepoint.com ) The final action is saving the updated filter so the duplicated dashboard preserves the modified widget logic. References/topics: Analytics, Dashboard Components, Edit Widgets, Widget Settings, GQL Filters, Custom/Duplicated Dashboards .
NEW QUESTION # 17
Anna created a complex GQL query that she plans on using weekly to filter the results and export the data for review. How can she store this query for repeated use?
Answer: B
NEW QUESTION # 18
You can configure your Forcepoint DSPM installation with Active Directory. What third-party product is used to import your AD users?
Answer: A
Explanation:
The correct answer is Keycloak . In Forcepoint DSPM standalone deployments, user authentication and user import workflows are handled through the embedded Keycloak administration console. The official Forcepoint DSPM documentation states that "AD Users are added to Forcepoint DSPM through Keycloak" and then describes the workflow for configuring Keycloak's User Federation capability. The process begins by opening the Keycloak admin console, logging in as an administrator, confirming that the gv realm is selected, navigating to User Federation , and adding an LDAP provider for the Active Directory source.
The distractors map to adjacent but incorrect concepts. User Federation is not the third-party product; it is the Keycloak feature used to connect LDAP or Active Directory identity stores. Kubernetes provides container orchestration and is not responsible for directory import. Rancher is used in platform or cluster management contexts, not AD identity synchronization. Okta can function as an identity provider in many enterprise environments, but it is not the specific product identified in the DSPM AD import workflow.
References/topics: User Management, Keycloak Administration, gv Realm, Active Directory Integration, LDAP Provider, User Federation .
NEW QUESTION # 19
What is the purpose of assigning compliance tags to data patterns in Forcepoint DSPM?
Answer: D
Explanation:
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 .
NEW QUESTION # 20
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