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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Features and Capabilities | 30% | - Configure and use AI Vector Search - Implement Select AI for natural language to SQL generation - Use Oracle Machine Learning within Autonomous Database - Apply AI-assisted performance tuning and optimization |
| Topic 2: Autonomous Database Architecture and Provisioning | 25% | - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Provision and configure Autonomous Database on shared infrastructure - Describe Autonomous Database architecture and core components - Provision and configure Autonomous Database on dedicated infrastructure |
| Topic 3: Security, Integration and Data Management | 20% | - Use Autonomous Database tools for development and administration - Configure identity and access management - Load, migrate and integrate data from various sources - Implement data encryption and security controls |
| Topic 4: Database Management and Operations | 25% | - Implement backup, recovery and high availability strategies - Monitor and manage database performance and resources - Perform patching, upgrades and lifecycle management - Configure auto-scaling and storage management |
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NEW QUESTION # 64
Which two statements are correct about Autonomous Data Warehouse on Shared Exadata Infrastructure?
Answer: A,C
Explanation:
Let’s evaluate each statement about Autonomous Data Warehouse (ADW) on Shared Exadata Infrastructure:
A . Oracle Database Result Cache is enabled by default for all SQL statements: True. ADW enables the Result Cache by default to improve query performance by storing frequently accessed results in memory.
B . You have direct access to the database node: False. ADW is a fully managed service; users do not have direct access to underlying nodes, which Oracle manages for patching, scaling, and security.
C . Parallelism is not enabled by default: False. Parallelism is enabled by default in ADW to optimize large analytical queries across multiple CPUs.
D . Compression is enabled by default. Autonomous Data Warehouse uses Hybrid Columnar Compression for all tables by default: True. Hybrid Columnar Compression (HCC) is applied automatically to reduce storage and enhance query performance.
Thus, A and D are correct, reflecting ADW’s default performance optimizations.
NEW QUESTION # 65
Which two license types does the customer need to benefit from BYOL when leveraging on-premise Enterprise Database licenses in Oracle Autonomous Database?
Answer: A,B
Explanation:
Full Detailed In-Depth Explanation:
Bring Your Own License (BYOL) allows using existing on-premises Oracle licenses in the cloud:
A: False. Exadata is included in Autonomous Database; no separate license is needed.
B: False. Active Data Guard is an optional feature, not required for BYOL.
C: True. RAC is needed for BYOL when scaling beyond 16 OCPUs, as Autonomous Database uses RAC for high availability in larger deployments.
D: True. Multitenant is mandatory, as Autonomous Database uses a multitenant architecture (CDB/PDB).
E: False. TDE is included by default, not a BYOL requirement.
NEW QUESTION # 66
What are three characteristics of Data Lake data captured in Object Storage? (Choose three.)
Answer: A,C,D
Explanation:
Data Lakes in OCI Object Storage store raw data for analysis. The three correct characteristics are:
Schema on read (C): Data Lakes store data in its raw, native format (e.g., JSON, CSV, Parquet) without a predefined schema. The schema is applied when data is read or processed, not when written, offering flexibility. For example, a Parquet file with sales data might be queried with SQL only when analyzed, not structured upfront like in a database.
Multiple subject areas (D): Data Lakes aggregate data from diverse sources—sales, HR, IoT—spanning multiple subject areas. This enables cross-domain analysis, like combining customer data with weather data for insights, all stored in a single OCI bucket.
Mixed data types (E): Data Lakes support varied formats: structured (e.g., CSV tables), semi-structured (e.g., JSON documents), and unstructured (e.g., videos). For instance, a bucket might hold CSV logs, JSON events, and image files, all accessible for processing.
The incorrect options are:
High concurrency (A): Data Lakes in Object Storage are not designed for high-concurrency transactional access (e.g., thousands of simultaneous updates). They’re optimized for batch processing or analytics, unlike ATP’s concurrency focus.
High transaction performance (B): Transactional performance (e.g., fast commits) is a database strength, not a Data Lake’s. Object Storage prioritizes scalability and durability over transactional speed, making it unsuitable for OLTP workloads.
These traits make Data Lakes ideal for big data analytics, not real-time transactions.
NEW QUESTION # 67
Which workload type does the Autonomous Database on dedicated infrastructure service currently support?
Answer: C
Explanation:
Autonomous Database on dedicated infrastructure supports multiple workload types. The correct answer is:
ATP and ADW (C): Autonomous Database on dedicated infrastructure supports both Autonomous Transaction Processing (ATP) for OLTP workloads (high concurrency, low latency) and Autonomous Data Warehouse (ADW) for analytical workloads (high throughput, complex queries). This dual support allows flexibility within a single dedicated Exadata infrastructure.
The incorrect options are:
Autonomous Transaction Processing only (A): Incorrect, as ADW is also supported.
Hybrid Columnar Compression (B): HCC is a data compression feature, not a workload type; it’s used within ADW but doesn’t define the workload.
Autonomous Data Warehouse only (D): Incorrect, as ATP is also supported.
This versatility is a key feature of dedicated deployments.
NEW QUESTION # 68
DBSRV1 is an Autonomous Database with the display name PRODDB. You plan to take manual backups of this database periodically. What must be the name of the bucket that will be used to store manual backups?
Answer: D
Explanation:
Manual backups in Autonomous Database are stored in OCI Object Storage, and the bucket name follows a strict convention. The correct name is:
BACKUP_DBSRV1 (D): For manual backups, ADB uses a bucket named BACKUP_<DB_UNIQUE_NAME> (all uppercase). Here, DBSRV1 is the database’s unique name (not the display name PRODDB), so the bucket must be BACKUP_DBSRV1. This bucket is automatically created by Oracle when you initiate a manual backup via the OCI console (e.g., “Create Manual Backup” button) or API (e.g., oci db autonomous-database backup create). For example, backing up DBSRV1 on March 18, 2025, stores files like backup_DBSRV1_20250318.dmp in this bucket. The unique name ensures uniqueness across the tenancy, as display names (e.g., PRODDB) might not be unique but the DB_UNIQUE_NAME is system-assigned and distinct.
The incorrect options are:
backup_proddb (A): This uses the display name proddb and lowercase, violating the BACKUP_<UNIQUE_NAME> uppercase convention.
BACKUP_PRODDB (B): While uppercase, it uses the display name PRODDB, not the unique name DBSRV1, so it’s incorrect. Display names are for human readability, not system identification.
backup_dbsrv1 (C): This uses lowercase and lacks the exact BACKUP_ prefix format, failing Oracle’s naming rule.
The rigid naming ensures consistency and automation in ADB’s backup system.
NEW QUESTION # 69
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