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| Section | Objectives |
|---|---|
| Topic 1: Security Configuration | - Data-security assignments - Users and groups - Object security - Security automation |
| Topic 2: Customization, Extensibility, Administration, and Maintenance | - AI and AIDP capabilities - Upgrades and releases - Security framework customization - User experience customization - Bundles for backup and restore - Incremental uploads and instance lifecycle activities - Semantic model extensions - Data Augmentation and External Applications - Test-to-production migration and bulk deployment |
| Topic 3: Oracle Fusion Data Intelligence Fundamentals | - Oracle Fusion Cloud Applications and Oracle Cloud Infrastructure concepts - Oracle Fusion Data Intelligence solution, capabilities, components, and functional architecture |
| Topic 4: Implementation Prerequisites and Instance Creation | - Ordering and activation requirements - FDI instance provisioning and configuration - Single Sign-On activation and Fusion Applications prerequisites - Oracle Cloud Infrastructure prerequisites and identity considerations - Private endpoint deployment considerations |
| Topic 5: Data Pipeline Configuration and Validation | - Functional areas - Data validation prerequisites - Preview and Generally Available features - Detailed and scheduled data-validation processes - Global and reporting parameters |
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NEW QUESTION # 36
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: B,C
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 # 37
Which preview feature predicts how long a data refresh will take to complete?
Answer: C
Explanation:
B Explanation: Documentation states: "This feature enables prediction of completion time for a data refresh.
You can see the predicted time under Data Pipeline in the Pipeline Parameters section on the Pipeline Settings page." Frequent Data Refresh (A) changes refresh cadence rather than predicting duration, Reset and Reload (C) discards and refetches all data, and Bulk Data Augmentation (D) batches non-Fusion extraction jobs - none of these forecast refresh time. Reference: Administering Oracle Fusion Data Intelligence - "About Data Refresh Performance
NEW QUESTION # 38
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 # 39
You are creating custom data security rules for five regional business units in Oracle Fusion Data Intelligence using five distinct data-type application roles. How does the Semantic Model Extensions framework organize these custom data security definitions within the customization pipeline?
Answer: C
Explanation:
D). Each data-type application role configuration generates exactly one customization step: Within the Semantic Model Extensions framework in Oracle Fusion Data Intelligence (FDI), administrators use the Configure Data Security task wizard to define row-level security filters. According to Oracle architecture guidelines, you can add and manage one customization step for each data role, meaning configuring five distinct data-type application roles yields five individual, discrete security customization steps in the pipeline.
Why the Incorrect Answers are Wrong
A). All custom data security definitions are combined into a single global system parameter: Security configurations for multiple roles are treated as discrete, independent rule-sets per application role rather than being merged into a single global parameter.
B). Security configurations are saved as unmanaged SQL scripts in Autonomous Data Warehouse: Security rules and configurations are managed natively within the FDI Console's metadata extension framework, not as unmanaged database-level SQL scripts.
C). Data security rules automatically generate an exported .DVA archive file in the Uploads Center: Data security configurations reside as internal metadata and semantic model security steps, not as automatic .DVA file exports inside the Uploads Center.
NEW QUESTION # 40
An implementation consultant is preparing to configure global pipeline settings for an integrated Oracle Fusion Data Intelligence deployment. The project team needs to ensure that core enterprise defaults for currency conversion, exchange rates, and transaction extraction start dates are properly established before launching data pipeline extraction.
Which TWO statements correctly describe the rules and behavior of Global Parameters in Oracle Fusion Data Intelligence?
Answer: A,D
Explanation:
Statement B: Global Parameters in Oracle Fusion Data Intelligence (FDI) govern system-wide baseline settings that apply universally across all active functional areas, including enterprise reporting standards like the Initial Extract Date and Target Currency.
Statement D: Because global settings dictate how data is extracted and transformed across the environment from day one, administrators must configure and save Global Parameters prior to activating functional areas and launching the initial data pipeline extraction.
Why the Incorrect Answers are Wrong
Statement A: Changing the Initial Extract Date after the pipeline has run does not automatically pull in prior historical years through an incremental extract; the parameter is locked and requires a data reset to adjust historical boundaries.
Statement C: Global Parameters must be configured before running data pipelines, not after initial execution.
Statement D (alternative interpretation) / E: Global parameters apply environment-wide and are managed under Data Configuration rather than being set on an isolated, subject-area-by-subject-area basis.
NEW QUESTION # 41
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