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| Section | Objectives |
|---|---|
| Topic 1: Forcepoint DSPM Architecture and Overview | - DSPM system components and platform overview - Deployment models (cloud / standalone) |
| Topic 2: Data Classification and Detection | - Pattern matching and classification models - Taxonomy and labeling mechanisms - Detectors and detector groups |
| Topic 3: Deployment and Installation | - Initial setup and configuration - Standalone DSPM deployment workflow - System requirements and prerequisites |
| Topic 4: Administration and User Management | - User federation and Active Directory integration - Role-based access control (RBAC) - User synchronization and management |
| Topic 5: Data Sources and Integration | - Streaming and event integration - SIEM and external integrations - Database discovery and structured data scanning - Configuring data sources |
| Topic 6: Monitoring, Analytics, and Reporting | - Scan progress and risk visibility - Data lineage and compliance monitoring - Dashboards and analytics widgets |
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질문 # 22
What is the primary purpose of the Scan Status dashboard in Forcepoint DSPM?
정답：D
설명：
The correct answer is D. To monitor the progress of ongoing data scans . The Scan Status dashboard is used to track scan execution and understand where a scan is in the discovery and classification lifecycle.
Forcepoint's scan analytics documentation describes scan status views that show the current discovery-stage status, last status update, discovered-file count, and detailed scan analytics for a selected data-source configuration. It also explains that the Scan Progress tab shows the selected scan configuration, discovery- stage status, last discovered file time, scan start time, scan number, classification status, and classification timing.
This makes the dashboard operationally useful for administrators who need to verify that scans are running, determine whether discovery or classification is still in progress, and identify whether scan activity has stalled or produced errors. It is not intended to display encrypted files, track department membership, or monitor network traffic. Department-level visibility is handled through Compliance Hub and Data Asset Inventory workflows, while network activity monitoring is outside the scope of the Scan Status dashboard. References
/topics: Dashboard, Scan Status, Scan Analytics, Scan Progress, Discovery Status, Classification Status, Data Source Scanning .
질문 # 23
The Forcepoint DSPM dashboards can simplify which of the following tasks? Select three.
정답：A,C,E
설명：
The correct selections are Identifying high-risk users , Identifying ROT data , and Identifying critical data assets . Forcepoint DSPM Analytics includes pre-defined dashboards, or boards, that summarize scan findings into operational views for security, compliance, and data-governance teams. Forcepoint states that Analytics boards present scan-derived metrics such as overexposed files, sensitive data, and data at risk, helping teams make informed decisions about vulnerabilities, risks, and compliance issues.
The pre-defined board list directly supports the three correct options. High Risk Users identifies users with excessive permissions or abnormal access patterns, supporting insider-threat reduction and least-privilege enforcement. ROT Data identifies redundant, obsolete, or trivial data so teams can reduce clutter, unnecessary exposure, and policy risk. Key Data Overview highlights critical data assets, allowing teams to prioritize protection of the organization's most valuable and sensitive information.
The other answers are not the best matches for dashboard simplification in this question. Database assets are handled through structured-data discovery and database-specific workflows, not the named dashboard use cases here. User credentials may be detected as sensitive content in scans, but identifying credentials is not listed as a primary pre-defined dashboard task. References/topics: Analytics, Pre-defined Boards, Data Classification, Data Hygiene, Data Risk, High Risk Users, ROT Data, Key Data Overview .
질문 # 24
You can configure your Forcepoint DSPM installation with Active Directory. What third-party product is used to import your AD users?
정답：E
설명：
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 .
질문 # 25
Which of the following statements is true about Forcepoint DSPM pattern matching?
정답：D
설명：
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 .
질문 # 26
Which of the following is a key benefit of defining a custom data taxonomy?
정답：C
설명：
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 .
질문 # 27
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