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| Section | Objectives |
|---|---|
| Administration and Operations | - Manage users and security - Scale compute and storage resources - Monitor database health and performance |
| Security and Integration | - Implement database security features - Automate administrative tasks - Integrate with Oracle Cloud services |
| Performance, Backup and Recovery | - Backup and restore operations - Performance tuning - High availability and disaster recovery |
| Provisioning and Deployment | - Create and provision Autonomous AI Database - Select workload type and deployment options - Configure networking and connectivity |
>> 1Z0-931-26 Übungsmaterialien <<
In dieser dynamischen Welt lohnt sich, etwas für berufliche Weiterentwicklung zu tun. Angesichts des Fachkräftemangels in vielen Branchen haben Sie mit einer Oracle 1Z0-931-26 (Oracle Autonomous AI Database Professional) Zertifizierung mehr Kontrolle über Ihren eigenen Werdegang und damit bessere Aufstiegschancen.
90. Frage
Which workload type does the Autonomous Database on dedicated infrastructure service currently support?
Antwort: C
Begründung:
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.
91. Frage
Which statement is FALSE about Data Insights?
Antwort: D
Begründung:
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.
92. Frage
Which two actions can you perform with Autonomous Data Guard enabled on Autonomous Database on Shared Infrastructure? (Choose two.)
Antwort: C,D
Begründung:
Autonomous Data Guard on Shared Infrastructure enhances ADB availability with standby databases. The two correct actions are:
Switchover (C): A switchover swaps roles between the primary and standby databases in a planned manner, with no data loss (RPO = 0). You initiate this via the OCI console (e.g., “Switchover” button on the primary ADB’s Data Guard section) or API (e.g., oci db autonomous-database switchover). For example, before maintenance on the primary, you switch to the standby in another region (e.g., from us-ashburn-1 to us-phoenix-1), taking ~2 minutes (RTO ≈ 2 min). This ensures continuity without downtime, as the standby becomes primary seamlessly.
Failover (D): A failover promotes the standby to primary during an unplanned outage (e.g., primary region failure), also with RPO = 0 due to synchronous replication. Trigger it via the OCI console (e.g., “Failover” on the standby) or API (e.g., oci db autonomous-database failover). For instance, if us-ashburn-1 crashes, the standby in us-phoenix-1 takes over in ~2 minutes, preserving all committed transactions. It’s automatic in some cases (e.g., severe failure), but manual initiation is supported too.
The incorrect options are:
View Apply Lag (A): While relevant in traditional Data Guard (measuring replication delay), Autonomous Data Guard on shared ADB uses synchronous replication (zero lag), and apply lag isn’t a user-actionable metric exposed in the UI—monitoring focuses on role status, not lag.
Reinstate (B): Reinstatement (restoring a failed primary as a standby) isn’t a user action in shared infrastructure. Oracle manages post-failover recovery, and users can’t manually reinstate; a new standby might be provisioned instead.
Change Protection Mode (E): Traditional Data Guard offers modes (e.g., Maximum Availability), but in Autonomous Data Guard on shared infrastructure, the mode is fixed (synchronous, akin to Maximum Availability), and users can’t modify it—control is limited to switchover/failover.
These actions ensure high availability with user-initiated role changes.
93. Frage
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?
Antwort: C
Begründung:
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.
94. Frage
Which two statements are true about Recovery Time Objective (RTO) and Recovery Point Objective (RPO) for Autonomous Data Guard? (Choose two.)
Antwort: C,D
Begründung:
Autonomous Data Guard enhances high availability for Autonomous Database. The two true statements are:
RPO is 0 minutes for an automatic failover (C): Recovery Point Objective (RPO) measures potential data loss. With Autonomous Data Guard, the standby database is synchronously replicated with the primary, ensuring zero data loss (RPO = 0) during an automatic failover, as all transactions are mirrored in real-time.
RTO is 2 minutes for an automatic failover (E): Recovery Time Objective (RTO) measures downtime during failover. For Autonomous Data Guard, Oracle specifies an RTO of approximately 2 minutes for automatic failovers, reflecting the time to detect failure and promote the standby to primary.
The incorrect options are:
RTO and RPO are adjustable through the OCI console (A): RTO and RPO are fixed by the Autonomous Data Guard architecture and cannot be manually adjusted via the OCI console.
RPO is adjustable, but RTO is always 5 minutes (B): RPO is not adjustable (it’s 0 due to synchronous replication), and RTO is not fixed at 5 minutes; it’s typically 2 minutes for automatic failover.
RTO and RPO are 0 minutes for manual failovers (D): Manual failovers (switchovers) have an RTO greater than 0 (typically a few minutes) due to manual initiation, though RPO remains 0 with synchronous replication.
These values ensure minimal disruption and data loss.
95. Frage
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