Accurate Hot Selling 1Z0-931-26 Exam Dumps 2026 Newly Released [Q68-Q90]

Fleet administrators manage resource utilization in Autonomous Database on Dedicated Infrastructure:
Correct Answer (B): Compartment quotas are used to set limits on OCPU usage across multiple database instances within a compartment. This OCI feature allows administrators to define maximum resource allocations, ensuring efficient use and cost control at a tenancy level.
Incorrect Options:
A: Oracle Machine Learning notebooks are for analytics, not resource control.
C: SQL Developer Web Console manages individual database tasks, not fleet-wide OCPU limits.
D: Resource Manager settings apply to individual instances, not fleet-level quotas.
Compartments provide a scalable, tenancy-wide control mechanism.

Oracle Data Safe enhances database security across various Oracle environments. The false statement is:
Oracle Data Safe only supports Autonomous Database (D): This is incorrect. Oracle Data Safe supports a wide range of Oracle databases, not just Autonomous Database. It works with Autonomous Database (shared and dedicated), Oracle Database Cloud Service (VM and Bare Metal), Exadata DB Systems, on-premises Oracle Databases, and Oracle Database on OCI Compute. For example, a DBA could use Data Safe to mask sensitive data in an on-premises 19c database or assess security in an Exadata Cloud@Customer deployment, not just ADB. This broad compatibility makes it a unified security tool across Oracle’s ecosystem.
The true statements are:
Oracle Data Safe helps you find sensitive data in your database by inspecting the actual data in your database and its data dictionary (A): Data Safe’s Data Discovery feature scans tables and metadata to identify sensitive columns (e.g., SSNs, credit card numbers), using predefined and custom patterns.
Oracle Data Safe helps you assess the security of your cloud database configurations by analyzing database configurations (B): The Security Assessment feature evaluates settings like encryption, auditing, and privileges, providing risk scores and recommendations.
Oracle Data Safe evaluates user types, how users are authenticated, and the password policies assigned to each user (C): User Assessment analyzes user accounts, authentication methods (e.g., password, SSO), and policies, highlighting risks like weak passwords.
The misconception in D limits Data Safe’s scope, which extends beyond ADB to all supported Oracle databases.

Oracle Data Pump is a powerful tool for migrating databases to Autonomous Database (ADB). The two correct advantages are:
Data Pump can exclude migration of objects like indexes and materialized views that are not needed by Autonomous Database (C): True. Data Pump’s EXCLUDE parameter allows skipping objects like indexes and materialized views during export (e.g., expdp … EXCLUDE=INDEX,MATERIALIZED_VIEW). In ADB, these objects are often redundant because the database automatically creates and manages them based on workload (e.g., auto-indexing). For example, exporting a schema with EXCLUDE=INDEX from an on-premises database reduces migration overhead, as ADB recreates necessary indexes post-import, optimizing for its managed environment. This flexibility minimizes unnecessary data transfer and speeds up the process.
Data Pump is platform-independent – it can migrate Oracle databases running on any platform (D): True. Data Pump uses a platform-agnostic dump file format (.dmp), enabling migration from any Oracle Database (e.g., on Linux, Windows, or Solaris) to ADB in the cloud. For instance, you could export from an Oracle 12c database on AIX, upload the dump to OCI Object Storage, and import it into ADB using DBMS_CLOUD.COPY_DATA, regardless of endianness or OS differences (handled by Data Pump’s conversion). This universality makes it ideal for heterogeneous migrations.
The incorrect options are:
Data Pump is faster to migrate database than using RMAN (A): False. Speed depends on context—RMAN (Recovery Manager) is faster for physical migrations (e.g., restoring backups) of entire databases, especially large ones, due to block-level copying. Data Pump, a logical migration tool, extracts and loads data row-by-row, which can be slower for massive datasets but offers more control (e.g., schema selection). No universal speed advantage exists; it’s workload-specific.
Data Pump creates the tablespaces used by your Autonomous Database (B): False. In ADB, tablespaces are fully managed by Oracle (e.g., DATA tablespace), and Data Pump doesn’t create them. It imports data into existing, pre-allocated storage, ignoring source tablespace definitions. E.g., a source tablespace USERS is mapped to ADB’s default storage, not recreated.
These advantages make Data Pump a versatile, tailored migration solution for ADB.

Oracle Database provides several techniques to optimize data access from Object Storage, particularly in the context of Autonomous Database, leveraging external tables and advanced storage formats. The question asks for four correct methods, and based on Oracle documentation, the following are the most applicable:
Correct Answer (A): Scan avoidance using partitioned external tables
Partitioned external tables allow Oracle Database to skip irrelevant partitions when querying data stored in Object Storage. By organizing data into partitions (e.g., by date or region), the database engine can prune partitions that don’t match the query predicates, significantly reducing the amount of data scanned and improving performance. This is a well-documented optimization for external data access in Oracle Database and Autonomous Database environments.
Correct Answer (D): Scan avoidance using columnar pruning for columnar stores like parquet and orc Columnar pruning is a technique where only the required columns are read from columnar file formats such as Parquet or ORC stored in Object Storage. These formats store data column-wise, enabling the database to avoid scanning entire rows or irrelevant columns, which is particularly efficient for analytical queries common in Autonomous Data Warehouse (ADW). This is a standard optimization supported by Oracle’s external table framework when accessing Object Storage.
Correct Answer (E): Optimized data archive using hybrid partitioned tables Hybrid partitioned tables combine local database partitions with external partitions stored in Object Storage. This allows older, less frequently accessed data to be archived efficiently in the cloud while remaining queryable alongside active data in the database. The database optimizes access by seamlessly integrating these partitions, reducing costs and improving archival efficiency. This feature is explicitly supported in Oracle Database and enhanced in Autonomous Database for data lifecycle management.
Correct Answer (F): Optimized data archive using partitioned external tables Similar to hybrid partitioned tables, using partitioned external tables alone optimizes data archiving by storing historical data in Object Storage with partitioning (e.g., by year). This method enables efficient querying of archived data by pruning unneeded partitions, offering a cost-effective and scalable archival solution. It’s a distinct approach from hybrid tables, focusing solely on external storage, and is widely used in Oracle environments.
Incorrect Options:
B . Scan avoidance using columnar pruning for .csv files
CSV files are row-based, not columnar, and lack the internal structure of formats like Parquet or ORC. While Oracle can read CSVs from Object Storage via external tables, columnar pruning is not applicable because CSVs don’t support column-wise storage or metadata for pruning. This makes this option incorrect as a specific optimization technique, though basic predicate pushdown might still reduce scanning to some extent.
C . Scan avoidance using block skipping when reading parquet and orc files Block skipping (or row group skipping) is a feature in some database systems where metadata in Parquet or ORC files allows skipping entire blocks of data based on query filters. While Oracle supports Parquet and ORC through external tables and can leverage their columnar nature (via pruning), “block skipping” is not explicitly highlighted as a primary optimization in Oracle’s documentation for Autonomous Database. It’s more commonly associated with systems like Apache Spark or Hive. Oracle’s focus is on columnar pruning and partitioning, making this option less accurate in this context.
Why Four Answers?
The question specifies “four ways,” and while six options are provided, A, D, E, and F are the most directly supported and documented methods in Oracle Autonomous Database for optimizing Object Storage access. Options B and C, while conceptually related to data access optimizations, are either inapplicable (CSV lacks columnar structure) or not explicitly emphasized (block skipping) in Oracle’s feature set for this purpose.
This selection aligns with Oracle’s focus on partitioning and columnar formats for efficient cloud data access, ensuring both performance and archival optimization.
External Tables and Object Storage
Hybrid Partitioned Tables
Autonomous Database Data Loading

Migrating a PDB to Autonomous Database has limitations:
Correct Answer (B): “PDBs cannot be migrated to an Autonomous Database using plug, unplug, or clone” is true. Autonomous Database does not support direct plugging/unplugging of PDBs due to its managed architecture and differing storage/backup mechanisms.
Incorrect Options:
A: Unplugging into an XML file is valid for traditional PDBs, but Autonomous Database doesn’t accept this for migration.
C: Cloning via database link isn’t a standard method; it’s more aligned with replication tools like GoldenGate.
D: PDB archives (e.g., .pdb files) are not supported for direct import into Autonomous Database.
Instead, use tools like Data Pump or GoldenGate for migration.

With Autonomous Data Guard enabled, the primary and standby databases are tightly coupled:
Correct Answer (C): “Standby database is also stopped” is true. When the primary database is stopped (e.g., via OCI Console), the standby database is also stopped to maintain consistency and alignment between the two. This ensures the standby remains a viable replica when the primary restarts.
Incorrect Options:
A: Switchover (role reversal) requires manual initiation and an active primary; it doesn’t occur automatically on stop.
B: The standby is not terminated; it remains configured but stopped.
D: Failover (standby promotion) is not automatic on a planned stop; it’s triggered only by primary failure.
This behavior preserves Data Guard functionality.

When creating a business model in Autonomous Database (e.g., via Data Modeler), advanced options enhance analytical capabilities:
Correct Answer (A): Autonomous Aggregate Cache uses dimensional metadata to manage caching, improving query performance.
Correct Answer (B): Analytic View Transparency View exposes analytic views as standard views for compatibility with existing tools.
Correct Answer (C): Analytic View Base Table Query Transformation enables seamless integration of analytic views into existing reports.
Incorrect Options:
D: “Display private tables” is not a recognized advanced option in this context.
E: “Business Object Security Feature” is unrelated to Autonomous Database business modeling.
These options optimize analytical workloads.

Viewing the maintenance history of Autonomous Exadata Infrastructure (AEI) requires navigating the OCI console correctly. The correct path is:
Under Solutions and Platforms then Platform Services then Autonomous Exadata (C): In the OCI console, AEI is categorized under “Solutions and Platforms” (a section for integrated services), then “Platform Services” (covering cloud platform offerings), and finally “Autonomous Exadata.” Here, you select your AEI instance (e.g., by name or OCID), and the details page displays a “Maintenance History” section listing past events (e.g., patching dates, durations, and statuses like “Completed on 2025-03-01”). For example, a quarterly RU applied on January 15 might show “Patch Applied: RU 23.1” with start/end times. This path reflects AEI’s role as a dedicated platform supporting Autonomous Container Databases (ACDs) and Autonomous Databases (ADBs).
The incorrect options are:
Under Core Infrastructure then Compute then Autonomous Exadata (A): “Core Infrastructure” > “Compute” is for virtual machines or bare metal hosts, not Exadata infrastructure. AEI isn’t a compute instance; it’s a database platform.
Under Database then Autonomous Transaction Processing then Autonomous Exadata (B): “Database” > “Autonomous Transaction Processing” focuses on ATP instances, not the underlying Exadata infrastructure. AEI maintenance is separate from specific ADB types.
Under Core Infrastructure then Autonomous Exadata (D): “Core Infrastructure” doesn’t directly list AEI; it’s too broad and lacks the “Platform Services” context needed for Exadata-specific management.
This navigation ensures you access AEI-specific maintenance details efficiently.

Creating an Autonomous Database offers specific deployment options. The two correct ones are:
APEX Service on Dedicated Infrastructure (A): This option provisions an Autonomous Database on dedicated Exadata infrastructure with Oracle Application Express (APEX) pre-installed and optimized. It’s ideal for APEX-based apps (e.g., custom web forms) requiring isolated resources. In the OCI console, you select “Dedicated Infrastructure” and “APEX Service” as the workload type, specifying OCPUs and storage. For example, a company might deploy an APEX app for internal reporting on a dedicated ACD, ensuring performance isolation from other tenants.
Autonomous JSON Database on Shared Infrastructure (C): This creates a schema-less, JSON-centric ADB on shared infrastructure, optimized for document storage (e.g., { "order_id": 123, "items": […] }). It’s provisioned via the OCI console under “Shared Infrastructure,” selecting “JSON Database” as the workload type. For instance, a mobile app might use it to store user data, leveraging SQL/JSON queries like SELECT JSON_VALUE(doc, '$.order_id'). It’s cost-effective and fully managed, sharing Exadata resources.
The incorrect options are:
APEX Service on Shared Infrastructure (B): There’s no distinct “APEX Service” workload type on shared infrastructure. APEX is available within ATP or ADW on shared infra, but it’s not a standalone option—you’d provision ATP and enable APEX manually, not as a dedicated “APEX Service.” Autonomous JSON Database on Dedicated Infrastructure (D): JSON Database is only offered on shared infrastructure, not dedicated. Dedicated options include ATP, ADW, and APEX Service, but JSON Database leverages shared resources for simplicity and cost.
These options cater to specific app development (APEX) and NoSQL (JSON) needs.

Full Detailed In-Depth Explanation:
The Oracle Autonomous JSON Database is a specialized service for managing JSON data with NoSQL-style capabilities. Let’s evaluate each statement:
A . It supports NoSQL-style, document-centric applications: True. Autonomous JSON Database is designed for NoSQL workloads, supporting document-based applications via APIs like SODA (Simple Oracle Document Access).
B . There is a 20 GB limit on JSON collection: False. The Oracle documentation does not specify a fixed 20 GB limit on JSON collections. Storage capacity is determined by the overall database size, which can scale dynamically without a specific cap on individual collections. This makes B the false statement.
C . JSON data is stored natively in the database: True. JSON data is stored in a binary format optimized for performance, avoiding the need for parsing or transformation during access.
D . You can promote Autonomous JSON Database to Autonomous Transaction Processing: True. Oracle allows promoting an Autonomous JSON Database to ATP, enabling relational capabilities if application needs evolve.
The false claim about a 20 GB limit likely stems from confusion with other database constraints, but no such restriction exists for JSON collections in Autonomous JSON Database.

Provisioning an Autonomous Database without using the OCI Console is possible through programmatic methods. The correct answer is:
Using the cloud infrastructure command line interface or REST API calls (D): The Oracle Cloud Infrastructure Command Line Interface (OCI CLI) and REST APIs allow users to provision and manage Autonomous Database resources programmatically. This method is ideal for automation or when GUI access is not preferred. For example, the OCI CLI command oci db autonomous-database create can be used to provision a database by specifying parameters like compartment ID, database name, and workload type. Similarly, a REST API POST request to /autonomousDatabases achieves the same result.
The incorrect options are:
Using the DBCA on the database server (A): The Database Configuration Assistant (DBCA) is a tool for on-premises Oracle databases, not for cloud-based Autonomous Databases, which are fully managed by Oracle.
Connecting to the cloud infrastructure console using the SSH wallet (B): SSH wallets are for secure shell access to compute instances, not for provisioning databases or interacting with the OCI Console.
It cannot be done (C): This is false, as programmatic provisioning via CLI or API is explicitly supported.
This capability enhances automation and integration into DevOps workflows.

Restoring an Autonomous Database involves specific recovery options:
Correct Answer (A): “Selecting the backup from which restore needs to be done” allows you to choose a specific automatic backup (listed by timestamp) in the OCI Console to restore the database to that state.
Correct Answer (D): “Specifying the point in time (timestamp) to restore” enables Point-in-Time Recovery (PITR), restoring to any moment within the backup retention period (default 60 days), even between backups.
Incorrect Options:
B: There’s no “snapshot of the backup” option; backups are managed as full/incremental sets, not user-selectable snapshots.
C: “Archived custom image” is not a feature of Autonomous Database restore; it applies to other OCI services like Compute.
These options provide flexibility for recovery scenarios.

Full Detailed In-Depth Explanation:
The Service Console in Autonomous Database is for database-level management:
A: False. Auto-scaling is managed via OCI console.
B: True. It allows monitoring and terminating runaway SQL statements.
C: False. Compartment moves are OCI console tasks.
D: False. Manual backups are initiated via OCI or SQL*Plus.

Oracle’s automatic indexing feature, available in Autonomous Database, optimizes query performance by creating and managing indexes. The requirement here is to enable it but ensure new indexes are invisible (not used by the optimizer unless explicitly made visible). The correct command is:
EXEC DBMS_AUTO_INDEX.CONFIGURE('AUTO_INDEX_MODE','REPORT ONLY') (C): The REPORT ONLY mode enables automatic indexing, where the database identifies and creates candidate indexes based on workload analysis. However, these indexes are created as invisible by default, meaning the optimizer does not use them in SQL execution plans unless a DBA manually makes them visible (e.g., via ALTER INDEX … VISIBLE). This mode is ideal for testing or validation without impacting production queries. For example, if a query frequently filters on a column, an invisible index might be created, but it won’t affect performance until explicitly activated.
The incorrect options are:
EXEC DBMS_AUTO_INDEX.CONFIGURE('AUTO_INDEX_MODE','IMPLEMENT') (A): The IMPLEMENT mode fully enables automatic indexing, creating and maintaining visible indexes that the optimizer uses immediately. This contradicts the requirement for invisible indexes.
EXEC DBMS_AUTO_INDEX.CONFIGURE('AUTO_INDEX_MODE','OFF') (B): The OFF mode disables automatic indexing entirely, so no indexes (visible or invisible) are created, failing the requirement to enable it.
EXEC DBMS_AUTO_INDEX.CONFIGURE('AUTO_INDEX_MODE','INVISIBLE') (D): There is no INVISIBLE mode in DBMS_AUTO_INDEX.CONFIGURE. While indexes can be set as invisible individually, this is not a valid configuration option for the auto-indexing feature.
The REPORT ONLY mode provides a controlled approach, allowing index creation for analysis without immediate deployment. This is particularly useful in Autonomous Database, where automation is balanced with DBA oversight.

Connecting an OCI Marketplace image (e.g., a compute instance running a preconfigured application) to a shared Autonomous Database (ADB) involves network configuration. The correct statement is:
Compute Image and Shared ADB must be in the same VCN and Subnet (A): For a compute instance from the OCI Marketplace to communicate with a shared Autonomous Database, both must reside in the same Virtual Cloud Network (VCN) and subnet. This ensures direct network connectivity without requiring complex routing or public internet traversal. By default, shared ADB instances use private endpoints within a VCN, and placing the compute instance in the same subnet allows seamless access using the database’s private IP address. For example, if the ADB is in subnet 10.0.1.0/24, the compute instance must also be in that subnet to connect via Oracle Net Services (e.g., using a wallet and tnsnames.ora).
The incorrect options are:
ADB must be configured with Private endpoints (B): While shared ADB instances are configured with private endpoints by default (not publicly accessible), this is not a configurable option you “must” set—it’s inherent to shared infrastructure. Thus, it’s not a requirement you actively enforce for this scenario; it’s already true.
ADB must be configured with NSG (C): Network Security Groups (NSGs) are optional for controlling traffic to an ADB. You can use NSGs for finer-grained security, but they are not mandatory; Security Lists at the subnet level can suffice. Hence, this is not a universal requirement for connectivity.
Cannot connect OCI Marketplace image to shared ADB (D): This is false. OCI Marketplace images (e.g., a web server or analytics tool) can connect to a shared ADB, provided network and authentication prerequisites (like same VCN/subnet and client credentials) are met.
This requirement simplifies network setup and enhances security by keeping communication internal to the VCN. For instance, a Marketplace image like a web application could query an ADB in the same subnet using JDBC or ODBC, leveraging the private endpoint.

Graph Studio in Autonomous Database enables graph creation and analysis:
Correct Answer (A): “Tables in an Autonomous Database instance” are used to create graphs. Graph Studio builds property graphs from relational tables by defining vertices (nodes) and edges (relationships) based on existing data, leveraging the database’s schema.
Incorrect Options:
B: Graph analytics algorithms analyze existing graphs, not create them.
C: NoSQL configuration is unrelated; Graph Studio uses relational data.
D: No external tool from oracle.com is required; Graph Studio is a built-in feature.
E: A license key isn’t a creation method; graph features are included with Autonomous Database.
This integrates graph capabilities with existing data.

The Data Load card in Database Actions (within ADB’s web interface) simplifies data loading. The false statement is:
You must first manually create your database credentials using DBMS_CLOUD.CREATE_CREDENTIAL before accessing your Oracle Object Storage Bucket (D): This is incorrect. The Data Load card automates credential management for Oracle Object Storage by leveraging the ADB instance’s IAM permissions. When you select an OCI Object Storage bucket in the UI, it uses the instance’s resource principal or user OCI credentials (e.g., from your signed-in OCI session), eliminating the need to manually run DBMS_CLOUD.CREATE_CREDENTIAL. For example, uploading sales.csv from a bucket via the Data Load card requires only bucket selection and file mapping—no PL/SQL credential setup. This automation enhances usability, contrasting with manual methods where CREATE_CREDENTIAL is needed (e.g., in SQL scripts).
The true statements are:
Data formats supported include: text, CSV, JSON, Avro, and Parquet (A): The Data Load card supports these formats, parsing them into tables using DBMS_CLOUD under the hood. E.g., a JSON file { "id": 1, "name": "John" } loads as rows.
Data can be loaded from a local data source (B): You can upload files directly from your local machine (e.g., a CSV on your desktop) via the browser interface, staging them temporarily for loading.
Data can be uploaded from several cloud storage sources including S3, Azure, Google Cloud, and Oracle Object Storage (C): The card supports these external cloud sources, requiring credentials (e.g., AWS keys), alongside native OCI Object Storage integration.
Data can be loaded from a remote database using Database Links (E): DBLinks allow pulling data from another Oracle database (e.g., INSERT INTO local_table SELECT * FROM remote_table@link), supported in the Data Load card.
The automation of credentials in D is a key differentiator for the UI-based Data Load feature.

The Always Free tier of Autonomous Database has specific limits. The two correct restrictions are:
Maximum of two Always Free Databases per OCI tenancy (B): OCI’s Always Free tier allows up to two free ADB instances per tenancy (e.g., one ATP, one ADW). This limit ensures fair resource distribution across users. For example, you might create FREEATP1 (1 OCPU, 20 GB) and FREEADW1 (1 OCPU, 20 GB) in your tenancy, but a third free instance isn’t permitted—you’d need a paid upgrade. This is tracked by tenancy OCID, visible in the OCI console under “Limits.” Maximum of one OCPU per Database (D): Each Always Free ADB is capped at 1 OCPU, non-scalable, with 20 GB of storage. This restricts compute power (e.g., no auto-scaling to 3x like paid tiers), suitable for small workloads like dev/test apps. For instance, a free ATP instance runs a lightweight app with SELECT * FROM users, but can’t handle heavy concurrency due to the single OCPU.
The incorrect options are:
Supports only ATP as a workload type (A): False. Always Free supports both ATP (transactional) and ADW (warehouse) workload types, giving flexibility for OLTP or analytics (e.g., ATP for a web app, ADW for reports).
Oracle Application Express (APEX) not included (C): False. APEX is included in both free ATP and ADW instances, pre-installed and accessible via the OCI console (e.g., “Development” > “APEX”). You can build apps like a task tracker without extra cost.
These restrictions balance free access with resource constraints, encouraging upgrades for heavier use.

The indexing pipeline in Oracle Text processes text for search:
Correct Answer (D): “Lexer” divides text into tokens (words, symbols) based on language rules and settings (e.g., whitespace, punctuation). It’s the stage responsible for tokenization in Oracle’s text indexing process.
Incorrect Options:
A: Sectioner identifies document sections (e.g., headers), not tokens.
B: Tokenizer is a generic term, but in Oracle Text, “Lexer” is the specific component.
C: Filter preprocesses text (e.g., removing stopwords), post-tokenization.
This step enables efficient text search capabilities.

Auto scaling in Autonomous Database dynamically adjusts OCPU usage up to three times the base allocation. Let’s evaluate each statement:
Correct Answer (C): “The base number of OCPU cores allocated to a database is not guaranteed” is false. The base OCPU count, set during provisioning or manual scaling, is always guaranteed as the minimum available resource, even with auto scaling enabled. Auto scaling only increases usage above this baseline when needed.
True Statements:
A: On dedicated Exadata, the max cores for auto scaling are constrained by available free cores not used by other databases, ensuring resource fairness.
B: The total cores in the Exadata instance define the upper limit for any database’s auto scaling capacity.
D: Auto scaling is not enabled by default (must be explicitly activated) and can be toggled on/off, though this statement’s phrasing could be clearer—it’s still true in context.
This guarantees predictable minimum performance while allowing flexibility for peak loads.

Customer-managed encryption keys enhance security control:
Correct Answer (A): “In a separate key vault external to the Exadata infrastructure” refers to OCI Vault (Key Management Service), where keys are securely stored and managed outside the database infrastructure.
Incorrect Options:
B: The wallet secures connections, not encryption keys.
C: Storing keys on Exadata compromises separation of duties.
D: Backups don’t store keys; they’re encrypted by keys from the vault.
This separation ensures robust key management.

Full Detailed In-Depth Explanation:
Since only four options are provided but the format requests two answers, I’ll assume E from a prior question context. Let’s evaluate:
A: True but conditional. Database Actions is accessible with a Private Endpoint, but requires proper network setup (e.g., VCN peering), not guaranteed by default.
B: True. Oracle APEX is accessed exclusively via the “Developer” menu in the Service Console, not other interfaces.
C: False. Oracle Machine Learning (OML) is available in both ADW and ATP, not just ADW.
D: False. Database Actions access requires specific user privileges (e.g., DWROLE), not granted to all users by default.
E (assumed): True. SQL Developer Web is exclusive to Autonomous Database, not traditional Oracle databases.
B and E are the most definitively true statements per documentation.

When creating an Autonomous Container Database (ACD) on dedicated infrastructure, Oracle offers specific patch types for maintenance. The correct answer is:
Release Update (RU) (D): During the creation of an ACD via the OCI console, users can choose to apply a Release Update (RU), which includes the latest security patches, bug fixes, and enhancements for the database version. RUs are the standard patching mechanism for Autonomous Databases on dedicated infrastructure, ensuring the system stays current.
The incorrect options are:
Quarterly Bundle Patch (QBP) (A): QBPs are not a recognized patch type for Autonomous Databases; they are more associated with on-premises Oracle deployments, not the cloud-native Autonomous infrastructure.
Prior Release Update Revision (PRUR) (B): PRURs are minor updates to prior releases, but they are not offered as a distinct option during ACD creation; Oracle focuses on RUs for consistency.
Prior Release Update (PRU) (C): PRUs refer to updates from previous major releases, but Autonomous Databases typically apply the latest RU, not prior ones, during provisioning or maintenance.
RUs align with Oracle’s strategy for maintaining Autonomous Databases.