2026 Actual Oracle 1Z0-1128-26 Dumps, Updated Exam Questions for Guaranteed Pass

1Z0-1128-26 free sample questions and answers

Oracle 1Z0-1128-26 practice quiz with correct answers for search indexing.

1. Question 1

   Which Fusion Applications duty role must be granted to the extraction user account to authorize data extractions via Business Intelligence Cloud Connector for Oracle Fusion Data Intelligence?

   ABICC_DATA_AUDIT_EXECUTIVE_PRIVATE_DUTY
   

   BBICC_PIPELINE_ADMINISTRATOR_PRIVATE_DUTY
   

   CBICC_EXTRACT_TRANSFORM_LOAD_TECHNICAL_PRIVATE
   

   DBICC_INTEGRATION_DEVELOPER_PRIVATE_DUTY
   

   Correct answer: C

   Comprehensive and Detailed Explanation From Oracle Fusion Data Intelligence / Course Guide Topics:

   C . BICC_EXTRACT_TRANSFORM_LOAD_TECHNICAL_PRIVATE.

   Explanation

   To perform and authorize data extractions using Business Intelligence Cloud Connector (BICC) for Oracle Fusion Data Intelligence (FDI / FAW) or external ETL pipelines, the extraction user account must be granted the duty role BICC_EXTRACT_TRANSFORM_LOAD_TECHNICAL_PRIVATE (ORA_BICC_EXTRACT_TRANSFORM_LOAD_TECHNICAL_PRIVATE).

   This role grants the necessary privileges to execute extraction jobs, query BICC REST APIs, and access the extracted data files from the storage location

   Oracle Study Guide reference area: Configuring Security

   
   

2. Question 2

   An admin user wants to use Bulk Data Augmentation to load several external, non-Fusion datasets that share the same connector, minimizing the number of extraction jobs needed.

   Which two statements accurately describe Bulk Data Augmentation?

   AIt submits a single extraction job covering multiple data stores to the Data Pipeline component.
   

   BIt requires each data store to use a different, unrelated connector.
   

   CIt supports Oracle Fusion Applications sources as well as external sources.
   

   DIt replaces the need for the Data Pipeline component entirely.
   

   EIt is especially useful for loading multiple external datasets that are functionally related, such as ledger or party entities.
   

   Correct answer: A, E

   Comprehensive and Detailed Explanation From Oracle Fusion Data Intelligence / Course Guide Topics:

   A and E

   Detailed Explanations of the Correct Options

   A . It submits a single extraction job covering multiple data stores to the Data Pipeline component: Bulk Data Augmentation allows administrators to group multiple data stores sharing the same connector into a single bundle, submitting them as one consolidated extraction job to the Data Pipeline framework to minimize management overhead.

   E . It is especially useful for loading multiple external datasets that are functionally related, such as ledger or party entities: The feature is engineered specifically to streamline the loading and management of groups of related external non-Fusion datasets, such as associated ledger or party entities.

   Detailed Explanations of the Incorrect Options

   B . It requires each data store to use a different, unrelated connector: This statement is false because Bulk Data Augmentation specifically requires all included data stores to share the same connector or data source.

   C . It supports Oracle Fusion Applications sources as well as external sources: This statement is incorrect because Bulk Data Augmentation is restricted exclusively to non-Fusion external data sources and does not support native Oracle Fusion Applications sources.

   D . It replaces the need for the Data Pipeline component entirely: This statement is wrong because Bulk Data Augmentation utilizes the Data Pipeline component to process and execute the bundled job rather than replacing it.

   Oracle Study Guide reference area: Configuring the Data Pipeline

   
   

3. Question 3

   Which Console area would you check if you need to see the available data-model and content patches for your FDI application and their auto-update target dates?

   AData Configuration
   

   BRelease Updates
   

   CBundle Repository
   

   DEnable Features
   

   Correct answer: B

   Comprehensive and Detailed Explanation From Oracle Fusion Data Intelligence / Course Guide Topics:

   Release Updates (B): This Console area provides visibility into scheduled content patches, data-model updates, and feature rollouts for your Fusion Data Intelligence (FDI) application, including their associated auto-update target dates.

   Explanation of the Incorrect Answers

   Data Configuration (A): This area manages functional area setups, data pipelines, and extraction parameters rather than release schedules and patch deployment timelines.

   Bundle Repository (C): This section handles the import and export of custom content migration packages, semantic model archives, and backup snapshots.

   Enable Features (D): This toggle menu is used to activate early-access, preview, or newly available features within the environment rather than reviewing update patches and timelines.

   Oracle Study Guide reference area: Administration and Maintenance

   
   

4. Question 4

   You observe that a scheduled data pipeline refresh job was in progress when a scheduled quarterly release update began on your FDI instance.

   What should you expect regarding the status and execution of the data pipeline job?

   AThe data pipeline job forces the release update to fail and aborts the upgrade process permanently.
   

   BThe data pipeline job bypasses the maintenance window and continues extracting source data without interruption.
   

   CThe data pipeline job is paused or canceled for the update duration and automatically resumes or restarts after the update completes.
   

   DThe data pipeline job automatically purges all historical transactional data in the staging schema.
   

   Correct answer: A

   Comprehensive and Detailed Explanation From Oracle Fusion Data Intelligence / Course Guide Topics:

   During a scheduled quarterly release update in Oracle Fusion Data Intelligence (FDI), the platform executes underlying data model upgrades and content patches. If a data pipeline refresh job is already active or conflicts with the maintenance window, the system manages the job lifecycle by pausing or canceling the ongoing extraction to prevent data corruption or schema lock conflicts. Once the zero-downtime application update finishes, the platform triggers post-update routines---including necessary incremental or full data refreshes---ensuring the environment seamlessly resumes data pipeline operations.

   Why the Other Options Are Incorrect

   A . The data pipeline job forces the release update to fail and aborts the upgrade process permanently: Standard platform maintenance and update mechanisms are designed with safeguards that take administrative precedence over routine user data pipelines, meaning an active pipeline cannot permanently abort a core Oracle cloud service upgrade.

   B . The data pipeline job bypasses the maintenance window and continues extracting source data without interruption: Data pipelines rely directly on the underlying data models and database structures that are actively being modified during a quarterly release update. They cannot bypass maintenance or run unaffected while schema changes are being applied.

   D . The data pipeline job automatically purges all historical transactional data in the staging schema: Application updates and pipeline refreshes update or ingest data based on upgrade timestamps and incremental rules; they do not indiscriminately or automatically wipe out historical transactional data stores in the staging or target data warehouse schema.

   Oracle Study Guide reference area: Configuring the Data Pipeline

   
   

5. Question 5

   Your FDI implementation includes AI/AIDP (Artificial Intelligence Data Platform) features that you want to leverage for predictive analytics. Before enabling these capabilities, what is the primary customization requirement you must address?

   AYou must configure custom data augmentation sources to provide the training datasets that AI/AIDP models require
   

   BYou must migrate all existing reports to a special AI-enabled reporting parameter set
   

   CYou must increase the global parameter memory allocation to accommodate AI processing overhead
   

   DYou must disable Data Security policies because AI/AIDP models cannot operate with row-level security restrictions
   

   Correct answer: A

   Leveraging AI/AIDP capabilities in FDI typically requires preparing appropriate training data and augmenting the semantic model with relevant data sources. Custom data augmentation is the mechanism used to extend FDI with external or derived datasets that train AI models and enable advanced analytics. While reporting parameters and global parameters are important configuration areas, they are not prerequisites for AI/AIDP enablement. Data security policies are fully compatible with AI/AIDP—in fact, ensuring that AI models respect data security boundaries is a critical requirement in production environments.