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| Section | Objectives |
|---|---|
| Functional Consultancy | - Business Requirements Analysis - Configuration and Validation - Implementation Decisions - Troubleshooting and Verification |
| Oracle Fusion Data Intelligence | - Analytics and Reporting - Instance Provisioning and Configuration - Data Augmentation - Data Pipelines and Data Loading - Administration and Configuration - Validation and Troubleshooting - Solution Overview and Architecture - Bundles, Backup and Restoration - Semantic Model Extensions and Customization - Security and Access Management |
| Oracle Cloud Infrastructure | - Security and Access - Cloud Infrastructure Configuration - OCI Concepts Relevant to Fusion Data Intelligence |
| Requirements Management | - Requirements Gathering - Implementation and Change Considerations - Requirements Analysis and Prioritization |
| Oracle Fusion Cloud Applications | - Fusion Cloud Applications Overview - Application Data and Business Processes - Integration with Fusion Data Intelligence |
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NEW QUESTION # 130
You are defining custom database objects in the Autonomous AI Lakehouse associated with your Oracle Fusion Data Intelligence instance to support a custom dataset data augmentation.
What is the standard suffix required for a Data Augmentation Dataset object to adhere to Oracle's database naming standards?
Answer: D
Explanation:
B). _DS: According to Oracle Fusion Data Intelligence database naming standards for the Autonomous Data Warehouse / AI Lakehouse, custom database objects and datasets must follow strict suffix guidelines.
Specifically, _DS is the required standard suffix designated for Data Augmentation Dataset objects (whereas
_EXT is used for Data Augmentation Extensions, _MD for Mini Dimensions, and _F for Facts).
Why the Incorrect Answers are Wrong
A). _EXT: This suffix designates a Data Augmentation Extension rather than a dataset object.
C). _MD: This suffix is reserved for Mini Dimensions in custom star schemas.
D). _F: This suffix is standard for Fact tables rather than data augmentation datasets.
NEW QUESTION # 131
You are preparing to import a bundle containing updated semantic model extensions into your Production environment, but the Production instance already contains existing custom subject areas created by another team.
What happens to the existing Production semantic model customizations when the imported bundle is applied?
Answer: A
Explanation:
Why Option C is Correct
When deploying a semantic extensions bundle into an environment containing existing modifications, Oracle Fusion Data Intelligence (FDI) supports a merge operation. This mechanism intelligently integrates new or updated semantic model components, custom subject areas, and extensions from the bundle with the pre- existing customizations already present in the target environment, preserving non-conflicting model steps rather than wiping out the entire environment.
Why the Other Options Are Incorrect
A). The imported bundle forces a hard database reset and deletes all Autonomous Data Warehouse staging tables: Importing an application or semantic bundle deals exclusively with application metadata and metadata repository configurations; it does not trigger a hard database reset or wipe transactional staging tables in the Autonomous Data Warehouse.
B). The import operation aborts immediately and revokes all active application role assignments: A valid bundle import passes validation checks and applies successfully without throwing immediate abort errors or stripping active user security role mappings.
D). The imported bundle overwrites OCI IAM identity domain security groups while leaving subject areas untouched: Semantic and content bundles target application-level artifacts and model layers rather than tenancy-wide OCI IAM identity domain security groups.
NEW QUESTION # 132
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,E
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 # 133
Which toggle controls whether the AWS S3 option appears in the Create Connection dialog?
Answer: A
Explanation:
C Explanation: Documentation lists a dedicated preview toggle for this connector: "On - Display the AWS S3 option in the Create Connection dialog. Off - Hide the AWS S3 option in the Create Connection dialog." Bulk Data Augmentation (A) and Frequent Refresh (B) are unrelated preview features, and the DFF Mapper (D) governs flexfield selection, not connector visibility. Reference: Administering Oracle Fusion Data Intelligence - preview features list
NEW QUESTION # 134
A lead analytics architect is designing a semantic model extension strategy for an enterprise FDI implementation. The project requires joining new transactional fact tables to standard dimensions, creating custom subject areas for business units, and ensuring all customizations can be safely migrated to Production.
Which TWO statements accurately describe the rules and capabilities of semantic model customization in Oracle Fusion Data Intelligence?
Answer: C,D
Explanation:
Why the Correct Statements are Right
Statement A: The Semantic Model Extensions framework in the FDI Console is the mandatory, architecturally supported method for defining custom logical joins, creating custom subject areas, and modifying presentation layers, ensuring customizations are handled within the platform's metadata governance model.
Statement C: The Promote Objects console task is the standardized administrative mechanism for moving validated artifacts, including semantic model extensions, from a tested non-production instance to a production instance.
Why the Incorrect Statements are Wrong
Statement B: Direct editing of system RPD files via tools like the Oracle Analytics Cloud Semantic Modeler (or legacy Model Administration Tool) within a production environment is not the supported path for FDI customizations; it would bypass the console-based governance framework and risk system instability during updates.
Statement D: External Application Merge operations are restricted to non-production instances to ensure that metadata integrations are properly vetted and tested before reaching a production environment.
Statement E: Modifying physical tables directly in the underlying Autonomous Data Warehouse (ADW) does not automatically propagate to the FDI presentation layer; all semantic changes (such as exposing new columns or tables) must be explicitly mapped and published through the Semantic Model Extensions framework to reflect in the analytics subject areas.
NEW QUESTION # 135
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