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Oracle 1Z0-931-26 Exam Syllabus Topics:

SectionObjectives
Provisioning and Deployment- Configure networking and connectivity
- Create and provision Autonomous AI Database
- Select workload type and deployment options
Performance, Backup and Recovery- High availability and disaster recovery
- Performance tuning
- Backup and restore operations
Security and Integration- Implement database security features
- Integrate with Oracle Cloud services
- Automate administrative tasks
Administration and Operations- Scale compute and storage resources
- Manage users and security
- Monitor database health and performance

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Oracle Autonomous AI Database Professional Sample Questions (Q28-Q33):

NEW QUESTION # 28
Which four levels of access can be defined in policies? (Choose four.)

Answer: A,B,D,E

Explanation:
Oracle Cloud Infrastructure (OCI) Identity and Access Management (IAM) defines four verb levels for policy permissions:
Read (B): Allows viewing resource details without modification (e.g., read autonomous-databases).
Manage (C): Permits full control, including creating, updating, and deleting resources (e.g., manage autonomous-databases).
Inspect (D): Enables listing resources and basic metadata without detailed access (e.g., inspect autonomous-databases).
Use (E): Allows interaction with resources (e.g., connecting to a database) without altering their configuration.
Incorrect Option:
Create (A): &#x201C;Create&#x201D; is not a standalone verb; it&#x2019;s part of the manage verb, which includes creation, update, and deletion actions.
These levels provide granular control over resource access in OCI.


NEW QUESTION # 29
As a database architect, you are tasked with configuring a high concurrency, production OLTP (EXAM) application to connect to an Autonomous Transaction Processing database with a requirement to have some reporting queries run in parallel mode. Which connection service is appropriate for such a workload?

Answer: A

Explanation:
Autonomous Transaction Processing (ATP) provides predefined connection services to optimize different workload types. For a high-concurrency OLTP application with parallel reporting queries, the appropriate service is:
HIGH (C): The HIGH connection service in ATP is designed for workloads requiring high concurrency and throughput, making it ideal for a production OLTP application like &quot;EXAM&quot; that handles many simultaneous transactions (e.g., user requests). Additionally, HIGH supports parallel query execution, which is critical for running reporting queries efficiently during off-peak times. It allocates more resources (e.g., OCPUs and I/O) compared to other services, ensuring performance for both transactional and analytical tasks. For example, the OLTP app might use HIGH to process thousands of concurrent user requests, while a nightly report leverages parallel processing to aggregate data quickly. In the wallet&#x2019;s tnsnames.ora, the HIGH service might look like exam_high = (DESCRIPTION=...), offering the best balance for this mixed workload.
The incorrect options are:
TPURGENT (A): The TPURGENT service prioritizes low-latency, time-critical transactions (e.g., sub-second response times for single-user actions). It&#x2019;s optimized for latency-sensitive operations, not high concurrency or parallel reporting, and would underperform for the broader OLTP and reporting needs here. For instance, it&#x2019;s better suited for a single critical transaction than a multi-user system.
TP (B): The TP (Transaction Processing) service is a general-purpose option for OLTP workloads, offering moderate concurrency and latency. However, it&#x2019;s not optimized for high concurrency or parallel query execution, making it less suitable for a production app with reporting demands. It&#x2019;s a middle ground, not a top-tier performer like HIGH.
MEDIUM (D): The MEDIUM service balances performance and resource usage for moderate workloads. It supports some concurrency but lacks the resource allocation and parallel execution capabilities of HIGH, making it inadequate for a high-concurrency OLTP system with reporting requirements.
The HIGH service&#x2019;s ability to handle both high transactional volume and parallel reporting aligns perfectly with the scenario&#x2019;s strict performance needs, all within ATP&#x2019;s zero-maintenance framework.


NEW QUESTION # 30
Which method does NOT permit you to change the database ADMIN user&apos;s password of an Oracle Autonomous Database on Shared Infrastructure?

Answer: D

Explanation:
Changing the ADMIN user&#x2019;s password in an Autonomous Database on Shared Infrastructure is restricted to specific managed methods due to its serverless nature:
Correct Answer (C): &#x201C;OS command line from the database server&#x201D; is not permitted because Autonomous Database is fully managed by Oracle. Users do not have direct access to the underlying operating system or server, eliminating this as a viable option.
Valid Methods:
A: The Admin page in the OCI Console allows password changes via the &#x201C;Change Administrator Password&#x201D; option, a user-friendly GUI method.
B: The OCI CLI supports password updates using commands like oci db autonomous-database update with the --admin-password parameter.
D: SQL Developer can change the password using an ALTER USER ADMIN IDENTIFIED BY &lt;new_password&gt; command, provided the user has appropriate credentials.
This restriction ensures security and consistency in a managed environment.


NEW QUESTION # 31
Which statement is FALSE about Data Insights?

Answer: D

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&#x2019;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&#x2019;t just a passive outcome of pre-existing database functions&#x2014;it&#x2019;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&#x2019;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 # 32
For someone that is not a service administrator to use SQL Developer Web, what package would you need to use to give them access?

Answer: C

Explanation:
SQL Developer Web in Autonomous Database relies on Oracle REST Data Services (ORDS) for access. The correct package is:
ORDS_ADMIN.ENABLE_SCHEMA (B): To allow a non-admin user (e.g., ANALYST1) to use SQL Developer Web, the ADMIN user executes ORDS_ADMIN.ENABLE_SCHEMA to enable the schema for ORDS access. This procedure activates the schema for RESTful services, granting privileges like CONNECT and SELECT implicitly for web-based SQL execution. Example:
BEGIN
ORDS_ADMIN.ENABLE_SCHEMA(p_schema =&gt; &apos;ANALYST1&apos;);
END;
After this, the user accesses SQL Developer Web via a URL (e.g., https://&lt;adb-host&gt;/ords/analyst1/_sdw), logging in with their database credentials. This is necessary because SQL Developer Web runs on ORDS, and only enabled schemas can interact with it. For instance, an analyst might query SELECT * FROM sales in the web interface post-enablement, without needing full admin rights.
The incorrect options are:
ORDS_ADMIN.GRANT_SCHEMA (A): No such procedure exists in ORDS_ADMIN. Granting is handled via database roles/privileges (e.g., GRANT CONNECT), not a specific ORDS grant function.
ORDS_PRIV.ENABLE_SCHEMA (C): There&#x2019;s no ORDS_PRIV package; this might confuse with ORDS_ADMIN. The correct package is ORDS_ADMIN for schema enablement.
SQLDEV_ADMIN.GRANT_SCHEMA (D): No SQLDEV_ADMIN package exists. SQL Developer Web access is managed through ORDS, not a separate SQL Developer-specific package.
ORDS_ADMIN.ENABLE_SCHEMA is the standard, secure way to enable non-admin access to this tool in ADB.


NEW QUESTION # 33
......

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