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| Section | Weight | Objectives |
|---|---|---|
| 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 |
| AI Features and Capabilities | 30% | - Use Oracle Machine Learning within Autonomous Database - Configure and use AI Vector Search - Implement Select AI for natural language to SQL generation - Apply AI-assisted performance tuning and optimization |
| Security, Integration and Data Management | 20% | - Use Autonomous Database tools for development and administration - Load, migrate and integrate data from various sources - Implement data encryption and security controls - Configure identity and access management |
| Autonomous Database Architecture and Provisioning | 25% | - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Provision and configure Autonomous Database on dedicated infrastructure - Provision and configure Autonomous Database on shared infrastructure - Describe Autonomous Database architecture and core components |
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NEW QUESTION # 25
Data Guard is enabled for your Autonomous Database and the Lifecycle State field for the primary database indicates that it is Stopped. Which statement is true?
Answer: C
Explanation:
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.
NEW QUESTION # 26
Which workload is particularly suited to Oracle Autonomous JSON Database?
Answer: D
Explanation:
Oracle Autonomous JSON Database is a specialized variant of Autonomous Database. The correct workload is:
Schema-less, document-centric (D): Autonomous JSON Database is designed for applications needing flexible, schema-less data storage and retrieval, particularly JSON documents. It’s a NoSQL-style database optimized for document-centric workloads, such as web or mobile apps storing user profiles, IoT data, or content management systems. For example, a social media app might store user posts as JSON documents { "user": "John", "post": "Hello world" }, allowing dynamic field additions without schema changes. It supports SQL/JSON queries (e.g., SELECT JSON_VALUE(doc, '$.user')), blending relational and NoSQL benefits, and auto-manages indexing for performance.
The incorrect options are:
Data Marts (A): Data marts are structured, analytical stores for aggregated data, better suited to Autonomous Data Warehouse (ADW), which excels at columnar storage and complex queries, not JSON’s flexible format.
Transactions (B): Traditional OLTP transactions (e.g., banking records) are the domain of Autonomous Transaction Processing (ATP), which uses rigid schemas for consistency, unlike JSON Database’s schema-less approach.
Data Lakes (C): Data lakes store raw, mixed-format data (e.g., JSON, CSV, Parquet) for later processing, typically in object storage, not a managed database like Autonomous JSON. While JSON Database handles JSON, it’s not a data lake replacement.
This workload leverages JSON Database’s agility for modern, unstructured data applications.
NEW QUESTION # 27
Which statement is FALSE about Data Insights?
Answer: A
Explanation:
Data Insights is a feature in Autonomous Database that helps users understand their data. The false statement is:
Data Insights are automatically generated by various analytic functions built into the database (C): This is incorrect. Data Insights are not solely the result of automatic execution of built-in analytic functions (e.g., AVG, SUM, or RANK). Instead, they are generated through a combination of user-initiated analysis and Oracle’s machine learning-driven capabilities within the Data Insights dashboard (part of Database Actions or OCI console). Users select datasets or tables, and the system applies algorithms to identify patterns (e.g., trends in sales) or anomalies (e.g., outlier transactions), but this process isn’t just a passive outcome of pre-existing database functions—it’s an active, curated feature requiring configuration. For example, a user might explore a SALES table, and Data Insights highlights a spike in Q4 sales, but this requires user input to define scope, not just automatic function output.
The true statements are:
Data Insights display information about patterns and anomalies in the data of entities in your Oracle Autonomous Database (A): True. The feature visualizes trends (e.g., seasonal sales increases) and outliers (e.g., unexpected data drops) in tables or views, helping users spot significant data behaviors. For instance, it might show a bar chart of monthly revenue with an anomaly flagged for a sudden dip.
Data Insights provides a wide range of graphical data presentation capabilities (B): True. It offers visualizations like bar charts, line graphs, and scatter plots, customizable to represent data insights effectively. E.g., a line graph might track customer sign-ups over time, with options to adjust axes or filters.
The results of the Insight analysis appear as a series of bar charts in the Data Insights dashboard (D): True, partially. While bar charts are a common default (e.g., comparing sales by region), the dashboard supports multiple chart types, but the statement’s focus on bar charts aligns with typical output for simple insights.
The misconception in C overlooks the interactive, ML-assisted nature of Data Insights, distinguishing it from passive function-based analytics.
NEW QUESTION # 28
Which set of Oracle Cloud Infrastructure metrics is available only for Autonomous Database on Dedicated Infrastructure?
Answer: B
Explanation:
Autonomous Database on Dedicated Infrastructure provides unique metrics due to its Exadata underpinnings:
Correct Answer (C): “IOPS, Storage used by tablespace, Apply and Transport Lag” are specific to dedicated deployments:
IOPS: Measures input/output operations per second, reflecting Exadata storage performance.
Storage used by tablespace: Tracks storage allocation at the tablespace level, unique to dedicated infrastructure’s granular control.
Apply and Transport Lag: Relevant for Data Guard configurations, showing replication delays, available only in dedicated setups with standby databases.
Incorrect Options:
A: Transaction Count, Running Statements, and Sessions are general metrics available in both shared and dedicated environments.
B: CPU and Storage Utilization are standard across all Autonomous Database types.
D: Query Latency, User Calls, and Execute Count are also common metrics, not exclusive to dedicated infrastructure.
These metrics offer deeper insights into dedicated Exadata performance.
NEW QUESTION # 29
An Autonomous Database user with an instance wallet has left the company. The user had shared a database user ID with other users when accessing the Autonomous Database. Other than changing the shared user password, what can an administrator do to protect the instance?
Answer: D
Explanation:
Securing an Autonomous Database after a user departs involves:
Correct Answer (C): “Rotate the instance wallet and share the new wallet with the remaining users” invalidates the old wallet’s credentials (e.g., certificates in ewallet.p12). Since the wallet secures client connections, rotating it ensures the departed user’s access is revoked, even if they retained a copy.
Incorrect Options:
A: Trusting the user is a security risk, not a solution.
B: Deleting the database user ID doesn’t address wallet-based access if credentials were shared externally.
D: Shutting down and restarting doesn’t revoke wallet access; it’s a temporary disruption.
This enhances security beyond password changes.
NEW QUESTION # 30
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