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100% Pass Oracle - 1Z0-931-25 - Newest Oracle Autonomous Database Cloud 2025 Professional Test Lab Questions

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Oracle 1Z0-931-25 Exam Syllabus Topics:

Topic
Details

Topic 1

• Managing and Maintaining Autonomous Database: This section of the exam measures the skills of Database Administrators and focuses on the ongoing management and maintenance of Autonomous Database instances. It includes using REST APIs and OCI CLI for automation, configuring access control lists and private endpoints, monitoring performance, setting up notifications, utilizing features like auto-indexing and data safe, handling connectivity through wallets and service handles, and configuring disaster recovery using Data Guard to ensure business continuity.

Topic 2

• Migrating to Autonomous Database: This section of the exam measures the skills of Cloud Migration Specialists and covers strategies for migrating existing databases to Autonomous Database. It includes understanding migration considerations, and available options, and using Oracle Data Pump to transfer data seamlessly while minimizing downtime, ensuring smooth transitions to Oracle Cloud infrastructure.

Topic 3

• Autonomous Database Dedicated: This section of the exam measures the skills of IT Architects and explores the workflows and functionality of Autonomous Database Dedicated and Autonomous Database Cloud@Customer. It includes provisioning dedicated resources, setting up OCI policies, monitoring infrastructure, scheduling maintenance tasks such as patching, and managing encryption keys for enhanced security. IT Architects will learn how to integrate dedicated database environments within their cloud strategy.

Topic 4

• Getting Started with Autonomous Database: This section of the exam measures the skills of Database Administrators and covers the architecture and key features of Oracle Autonomous Database. It explains how the database integrates within the Oracle ecosystem and provides an overview of different Autonomous Database offerings and their licensing models, helping administrators understand how to deploy and manage these cloud-based databases efficiently.

 

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Oracle Autonomous Database Cloud 2025 Professional Sample Questions (Q118-Q123):

NEW QUESTION # 118
Which statement is FALSE about Data Insights?

• A. Data Insights are automatically generated by various analytic functions built into the database
• B. The results of the Insight analysis appear as a series of bar charts in the Data Insights dashboard
• C. Data Insights provides a wide range of graphical data presentation capabilities
• D. Data Insights display information about patterns and anomalies in the data of entities in your Oracle Autonomous Database

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 # 119
Which three advanced options can you enable or disable while creating a business model? (Choose three.)

• A. Analytic View Transparency View
• B. Business Object Security Feature
• C. Display private tables
• D. Analytic View Base Table Query Transformation
• E. Autonomous Aggregate Cache

Answer: A,D,E

Explanation:
When creating a business model in Autonomous Database (e.g., via Data Modeler), advanced options enhance analytical capabilities:
Correct Answer (A): Autonomous Aggregate Cache uses dimensional metadata to manage caching, improving query performance.
Correct Answer (B): Analytic View Transparency View exposes analytic views as standard views for compatibility with existing tools.
Correct Answer (C): Analytic View Base Table Query Transformation enables seamless integration of analytic views into existing reports.
Incorrect Options:
D: "Display private tables" is not a recognized advanced option in this context.
E: "Business Object Security Feature" is unrelated to Autonomous Database business modeling.
These options optimize analytical workloads.

 

NEW QUESTION # 120
You created an Autonomous Database without auto scaling. Which two ways can you enable auto scaling? (Choose two.)

• A. Use a REST call to shut down the instance, then a second REST call to enable Auto Scaling, and a REST call to restart the instance.
• B. Click Scale Up/Down and select the Auto Scaling checkbox.
• C. Shut down the instance, click Scale Up/Down and select the Auto Scaling checkbox, then restart the instance.
• D. Use a REST call to enable Auto Scaling.

Answer: B,D

Explanation:
Enabling auto scaling on an existing Autonomous Database can be done without unnecessary complexity:
Correct Answer (A): "Click Scale Up/Down and select the Auto Scaling checkbox" is the simplest GUI method. In the OCI Console, navigate to the database, select "Scale Up/Down," and enable the auto scaling option, allowing up to 3x the base OCPUs dynamically.
Correct Answer (C): "Use a REST call to enable Auto Scaling" leverages the OCI REST API to update the database configuration with the isAutoScalingEnabled parameter set to true. This is ideal for programmatic control.
Incorrect Options:
B: Shutting down the instance is unnecessary; auto scaling can be enabled while the database is running.
D: Multiple REST calls, including shutdown and restart, overcomplicate the process when a single API call suffices.
These methods ensure minimal disruption and efficient resource management.

 

NEW QUESTION # 121
Which workload is particularly suited to Oracle Autonomous JSON Database?

• A. Data Lakes
• B. Transactions
• C. Data Marts
• D. Schema-less, document-centric

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 # 122
You see a clock icon in the Status column on the SQL Monitoring tab of Performance Hub. What does it indicate?

• A. The SQL statement is executing.
• B. The SQL statement is queued.
• C. The SQL statement did not complete either due to an error.
• D. The SQL statement completed its execution.

Answer: B

Explanation:
The Performance Hub in Autonomous Database provides real-time SQL monitoring with status indicators:
Correct Answer (A): A clock icon in the Status column indicates "The SQL statement is queued." This means the statement is waiting in a queue (e.g., due to resource limits or consumer group settings) and has not yet started executing.
Incorrect Options:
B: An executing statement typically shows a green progress bar or running icon, not a clock.
C: An error would display a red icon or error symbol, often with details in the UI.
D: A completed statement shows a checkmark or similar success indicator.
This visual cue helps identify resource contention or scheduling delays.

 

NEW QUESTION # 123
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