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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Database Management and Operations | 25% | - Configure auto-scaling and storage management - Implement backup, recovery and high availability strategies - Monitor and manage database performance and resources - Perform patching, upgrades and lifecycle management |
| Topic 2: AI Features and Capabilities | 30% | - Implement Select AI for natural language to SQL generation - Use Oracle Machine Learning within Autonomous Database - Configure and use AI Vector Search - Apply AI-assisted performance tuning and optimization |
| Topic 3: Autonomous Database Architecture and Provisioning | 25% | - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Provision and configure Autonomous Database on dedicated infrastructure - Describe Autonomous Database architecture and core components - Provision and configure Autonomous Database on shared infrastructure |
| Topic 4: Security, Integration and Data Management | 20% | - Load, migrate and integrate data from various sources - Use Autonomous Database tools for development and administration - Implement data encryption and security controls - Configure identity and access management |
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NEW QUESTION # 33
Which two methods can you use to create database users and grant roles in Autonomous Database services?
Answer: A,D
Explanation:
Full Detailed In-Depth Explanation:
User and role management in Autonomous Database:
A: False. OCI console manages infrastructure, not database users.
B: True. SQL Developer provides a GUI for user/role administration.
C: False. DBMS_CLOUDADMIN is for cloud-specific tasks, not user creation.
D: True. SQL*Plus allows direct SQL commands for user/role management.
NEW QUESTION # 34
Which three security features are available in Oracle Autonomous Database Shared Infrastructure? (Choose three.)
Answer: A,B,E
Explanation:
Oracle Autonomous Database Shared Infrastructure offers built-in security features to protect data and ensure compliance. The three correct features are:
Customer Managed Keys (A): This feature allows customers to use their own encryption keys for Transparent Data Encryption (TDE), stored in Oracle Key Vault or OCI Vault. It gives control over key management, enhancing security by ensuring only the customer can decrypt data. For example, a company might generate a key in OCI Vault, link it to their ADB, and rotate it periodically, all managed outside Oracle’s default keys.
Database Vault (D): Oracle Database Vault enforces fine-grained access controls, preventing unauthorized access to sensitive data even by privileged users (e.g., DBAs). In ADB shared infrastructure, it’s available to restrict operations like SELECT on specific schemas, adding a layer of protection against internal threats. For instance, it could block an admin from viewing customer PII unless explicitly permitted.
Transparent Data Encryption (E): TDE is enabled by default in Autonomous Database, encrypting data at rest (e.g., in tablespaces, backups, and logs) using AES-256. This ensures that if physical storage is compromised, the data remains unreadable without the encryption key. Customers can opt for customer-managed keys (A) or use Oracle-managed keys, but TDE itself is always active.
The incorrect options are:
Audit Vault (B): Oracle Audit Vault is a separate product for centralized audit log management, not a built-in feature of ADB shared infrastructure. While ADB performs auditing, it doesn’t include Audit Vault’s advanced capabilities natively.
Data Redaction (C): Data Redaction (masking sensitive data in query results) is available in on-premises Oracle Database Enterprise Edition but is not supported in Autonomous Database shared infrastructure. ADB’s managed nature limits such custom configurations, relying instead on TDE and Database Vault for security.
These features collectively ensure robust security with minimal customer effort in a shared environment.
NEW QUESTION # 35
In which four ways can Oracle Database optimally access data in Object Storage? (Choose four.)
Answer: A,C,D,F
Explanation:
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
NEW QUESTION # 36
While provisioning a dedicated Autonomous Container Database, which backup retention period CANNOT be implemented?
Answer: B
Explanation:
Full Detailed In-Depth Explanation:
When provisioning an Autonomous Container Database (ACD) on dedicated infrastructure, Oracle provides specific options for backup retention periods to balance data recovery needs with storage costs. According to the official Oracle documentation, the available backup retention periods for a dedicated ACD are:
7 days: This is the default retention period for a newly provisioned ACD.
15 days: An option for extended retention beyond the default.
60 days: The maximum supported retention period for ACDs, offering the longest recovery window.
The option of 120 days is not supported as a backup retention period for an Autonomous Container Database. This limitation is due to the design of the Autonomous Database service, which caps retention at 60 days to optimize storage and performance on dedicated Exadata infrastructure. Attempting to set a retention period beyond 60 days is not an available choice during provisioning. Users must select a retention period that meets their recovery point objectives (RPO) within these constraints, noting that longer retention increases storage usage and associated costs.
NEW QUESTION # 37
Which of the following is not required for connecting to Autonomous Database (ADB) via SQL Developer?
Answer: E
Explanation:
Connecting to Autonomous Database (ADB) via SQL Developer requires specific parameters. The correct answer is:
Connection Name (E): The Connection Name is a user-defined label in SQL Developer to identify the connection in the tool’s interface. It is not a technical requirement for establishing the database connection itself, making it optional in terms of connectivity.
The required parameters are:
Password (A): Essential for user authentication alongside the username.
Service (B): Refers to the service name (e.g., high, medium, low) from the wallet’s tnsnames.ora, specifying the performance level and connection type.
Username (C): Required to identify the database user.
Database name (D): Needed to specify the target database or PDB within the ADB instance, typically provided via the wallet configuration.
Without A, B, C, and D, the connection cannot be established, but E is merely a convenience.
NEW QUESTION # 38
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