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| Section | Objectives |
|---|---|
| Data Pipeline Configuration and Validation | - Data validation prerequisites - Preview and Generally Available features - Global and reporting parameters - Functional areas - Detailed and scheduled data-validation processes |
| Customization, Extensibility, Administration, and Maintenance | - AI and AIDP capabilities - Data Augmentation and External Applications - Test-to-production migration and bulk deployment - Bundles for backup and restore - Incremental uploads and instance lifecycle activities - Semantic model extensions - Security framework customization - Upgrades and releases - User experience customization |
| Implementation Prerequisites and Instance Creation | - Single Sign-On activation and Fusion Applications prerequisites - Private endpoint deployment considerations - Ordering and activation requirements - Oracle Cloud Infrastructure prerequisites and identity considerations - FDI instance provisioning and configuration |
| Security Configuration | - Users and groups - Data-security assignments - Object security - Security automation |
| Oracle Fusion Data Intelligence Fundamentals | - Oracle Fusion Data Intelligence solution, capabilities, components, and functional architecture - Oracle Fusion Cloud Applications and Oracle Cloud Infrastructure concepts |
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NEW QUESTION # 54
You are customizing an Overview Dashboard in Oracle Fusion Data Intelligence to display executive performance summaries with tailored metric targets, conditional formatting, and associated dimensions.
Which reusable business object construct should you configure to serve as the foundation for these overview composite visualizations?
Answer: D
Explanation:
D). Key Metrics: In Oracle Fusion Data Intelligence (FDI), Key Metrics are the standardized, reusable business object constructs designed specifically to serve as the foundation for executive dashboards and overview visualizations. They encapsulate business logic, aggregation rules, and targets, ensuring consistency across composite visualizations, KPI cards, and performance summaries.
Why the Incorrect Answers are Wrong
A). Pipeline Parameters: These are configuration settings used to control the behavior of the data extraction pipelines (such as functional area scopes or ledger filters), rather than serving as foundational objects for dashboard visualizations.
B). Data Augmentations: This feature is used to extend the semantic data model by incorporating additional attributes or custom columns from source applications into existing star schemas, not for defining business- level KPIs for dashboard display.
C). Access Control Rules: These define the data security and row-level access permissions for users, ensuring they see only the data they are authorized to view; they do not function as the structural building blocks for visualizations.
NEW QUESTION # 55
An author user in Oracle Fusion Data Intelligence is preparing a subject area dataset so that non-technical consumer users can use natural language prompts in the Oracle Analytics AI Assistant to explore business metrics. The author user needs to ensure business terms commonly used by regional teams are recognized by the assistant while maintaining optimal search performance.
Which TWO configuration actions should the author user take during data preparation?
Answer: C,D
Explanation:
Statement B (Add common business synonyms...): To ensure regional or alternative business terms are successfully recognized by natural language prompts, authors must configure custom synonyms mapped directly to the appropriate attribute columns, allowing the AI Assistant to bridge user vocabulary with underlying database objects.
Statement D (Build search indexes for essential dimension attributes...): Optimizing search performance while keeping the model accurate requires focusing search indexing efforts exclusively on essential dimensions and measures, reducing noise and search overhead from bloated or irrelevant columns.
Why the Incorrect Answers are Wrong
Statement A: Logical layer metadata is managed natively through semantic model development and console tooling rather than manual CSV exports and uploads via the Uploads center.
Statement C: Private endpoints secure internal network traffic between cloud components, but they are not a configuration step for managing vector embeddings or natural language synonyms.
Statement E: Re-activating core functional areas is a pipeline configuration task that forces full extractions; it does not selectively optimize or refresh semantic search caches for natural language assistants.
NEW QUESTION # 56
Which access control feature, when enabled in Fusion Cloud Applications, requires extraction and validation roles to be public?
Answer: D
Explanation:
When Location Based Access Control (LBAC) is enabled in an Oracle Fusion Cloud Applications source instance, access to applications and tasks is strictly filtered based on registered IP addresses and network locations. Because data extraction and validation pipelines run automated integration services that may originate outside typical user network perimeters, Oracle requires that the specific roles assigned to users performing data extraction and validation must be explicitly designated as public (accessible from all IP locations) to ensure pipelines can execute successfully without being blocked by network-level access restrictions.
Why the Other Options Are Incorrect
A). Configurable Security Context: This mechanism manages dynamic data and context parameters during transactional processing rather than controlling network-based IP restrictions that mandate public role configurations.
B). Row-Level Security: Row-level security restricts data visibility at the table row level based on criteria such as business unit or department assignments, rather than governing network accessibility or role-to-IP permissions.
C). Auto Sync Security: Auto sync security handles the automated synchronization of user accounts, groups, and roles between source applications and FDI, rather than handling network or location-based access rules.
NEW QUESTION # 57
An implementation team is preparing to execute data validation tests comparing metrics in Oracle Fusion Data Intelligence against Oracle Transactional Business Intelligence (OTBI). The lead consultant needs to verify that all prerequisite user setups, security roles, and credential configurations are correctly in place before creating validation sets. Which TWO actions are mandatory prerequisites for executing data validation in this environment?
Answer: A,B
Explanation:
A). Create a custom BI Abstract role and assign it to the dedicated validation user in Oracle Fusion Cloud Applications: To ensure the validation user can retrieve the necessary metrics from OTBI for comparison, they must be provisioned with the appropriate BI Abstract role within the source Oracle Fusion Cloud Applications environment.
C). Ensure the validation user exists in both FDI and Fusion Applications with identical data security privileges: It is a core requirement that the dedicated validation user accounts in both the source Fusion Applications and the FDI instance hold equivalent data security access privileges to ensure the accuracy and alignment of the data being compared.
Why the Incorrect Answers are Wrong
B). Deploy a private endpoint in OCI before enabling the Data Validation console tile: While networking configurations are important, deploying a private endpoint is not a functional prerequisite for enabling the Data Validation console tile.
D). Configure row-level data security filters within the Object Permissions tab of Semantic Model Extensions:
Validation relies on comparing aggregated source metrics against warehouse data; row-level security configuration in the semantic model is not a mandatory prerequisite for setting up validation sets.
E). Reset the Autonomous Data Warehouse admin password before saving Source Credentials: The Source Credentials tab is used to configure application-level source authentication (such as the validation user credentials for Fusion Applications), not database-level administrative passwords for the Autonomous Data Warehouse.
NEW QUESTION # 58
You are configuring Oracle Fusion ERP Analytics and need to restrict which ledgers, payables business units, and receivables business units are visible to a group of users, based on the data role mapped to their group.
Which configuration would you use to accomplish this?
Answer: C
Explanation:
Explanation of the Correct Answer
Reporting Parameters combined with Security Assignments (C): To successfully restrict which ledgers, payables business units, and receivables business units are visible to a group of users based on their mapped data roles, you must configure the Enterprise Resource Planning report parameters to target those specific values and combine them with user-level security assignments to enforce data-level filters in the semantic layer.
Explanation of the Incorrect Answers
Global Parameters (A): These parameters control high-level platform configuration settings-such as global currencies and initial data extraction dates-rather than handling role-based data access restrictions for organizational units.
Preview Features (B): This mechanism allows administrators to toggle and evaluate experimental or early- release platform capabilities rather than managing enterprise financial security configurations.
Bundle Deployment (D): This function is utilized for migrating or deploying custom semantic models, presentation objects, and configuration bundles between different environments rather than assigning security permissions to users.
NEW QUESTION # 59
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