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| Section | Objectives |
|---|---|
| Topic 1: Provisioning and Deployment | - Configure networking and connectivity - Select workload type and deployment options - Create and provision Autonomous AI Database |
| Topic 2: Performance, Backup and Recovery | - Backup and restore operations - High availability and disaster recovery - Performance tuning |
| Topic 3: Security and Integration | - Implement database security features - Automate administrative tasks - Integrate with Oracle Cloud services |
| Topic 4: Administration and Operations | - Manage users and security - Monitor database health and performance - Scale compute and storage resources |
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NEW QUESTION # 93
Which statement is FALSE about Autonomous Database maintenance on Dedicated Infrastructure?
Answer: A
Explanation:
Full Detailed In-Depth Explanation:
Maintenance on dedicated infrastructure:
A: True. You can adjust maintenance windows for container databases.
B: False. Exadata Infrastructure maintenance (e.g., OS, grid patching) is separate from container database patching, which occurs independently.
C: True. Oracle reschedules missed maintenance to the next quarter.
D: True. Infrastructure maintenance occurs quarterly.
NEW QUESTION # 94
A customer wants to increase the throughput of their inserts. They have discovered that the bottleneck is in the storage I/Os of their environment. What should they do to remove this bottleneck?
Answer: A
Explanation:
Addressing a storage I/O bottleneck for insert throughput in Autonomous Database involves resource adjustments:
Correct Answer (C): “Increase the number of OCPUs allocated to the database” boosts processing power, which directly improves I/O performance. In Autonomous Database, OCPUs handle both compute and I/O operations; more OCPUs increase the I/O bandwidth, reducing the bottleneck for insert-heavy workloads.
Incorrect Options:
A: Removing non-JSON data may optimize storage use but doesn’t directly address I/O throughput for inserts.
B: “Noisy neighbors” is a shared infrastructure concern, but migration isn’t a standard solution for I/O bottlenecks and requires Oracle intervention, not user control.
D: There is no DBMS_CLOUD.INCREASE_THROUGHPUT procedure; this is a fabricated option.
Scaling OCPUs is the most effective user-controlled solution.
NEW QUESTION # 95
Your customer has upgraded their on-premises 11.2 Database to 12.2. During this migration, the database was migrated to a pluggable database (PDB) and is now in production. How should the customer unplug their database to migrate to an Autonomous Database?
Answer: C
Explanation:
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.
NEW QUESTION # 96
Which statement is FALSE about Data Insights?
Answer: B
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 # 97
Which statement is FALSE regarding provisioning an Autonomous Database and configuring private endpoints with security rules to allow incoming and outgoing traffic to and from the Autonomous Database instance?
Answer: C
NEW QUESTION # 98
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