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Professional 1Z0-931-25 - Latest Oracle Autonomous Database Cloud 2025 Professional Exam Materials

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Oracle 1Z0-931-25 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 3

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 4

Autonomous Database Tools: This section of the exam measures the skills of Data Analysts and covers the tools available within Autonomous Databases for advanced data processing and analytics. It includes Oracle Machine Learning, APEX, and SQL Developer Web for database development, as well as data transformation, business model creation, data insights, and data analysis, allowing analysts to extract valuable insights from large datasets.

Topic 5

Autonomous Database Shared: This section of the exam measures the skills of Cloud Engineers and focuses on creating and managing shared Autonomous Database instances. It includes provisioning, scaling, and starting or stopping instances, as well as database consolidation with Elastic Resource Pools. It also covers user management, cloning, database migration, monitoring, backup and restore processes, and introduces Data Guard for high availability, ensuring cloud engineers can maintain optimal database performance.

Topic 6

Developing on Autonomous Database: This section of the exam measures the skills of Application Developers and focuses on developing and extending applications using Autonomous Database. It covers using generative AI for natural language queries, Autonomous JSON Database, Oracle Text for document search, location-based analysis with Autonomous Spatial, Autonomous Graph for data relationships, and integration with Object Storage, enabling developers to build intelligent, scalable applications.

Topic 7

Data Lake Analytics with Autonomous Database: This section of the exam measures the skills of Big Data Engineers and explores how Autonomous Database can be used for analytics in data lake environments. It includes data ingestion, query optimization, and leveraging cloud-native analytics services, ensuring engineers can efficiently process and analyze large volumes of structured and unstructured data.

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Oracle Autonomous Database Cloud 2025 Professional Sample Questions (Q17-Q22):

NEW QUESTION # 17
Which can be used to ensure that your Autonomous Database is accessible only from a given set of IPs?

A. Access Control List
B. IP Vault
C. Security List
D. IPSec List

Answer: A

Explanation:
Restricting access to an Autonomous Database to specific IPs involves network security controls. The correct answer is:
Access Control List (C): In Autonomous Database, an Access Control List (ACL) defines which IP addresses or CIDR blocks (e.g., 192.168.1.0/24) can connect to the database. You configure this via the OCI console under the ADB's "Access Control List" settings, adding rules like "Allow TCP from 10.0.0.0/16 on port 1522." This applies to public endpoints (shared infrastructure) or private endpoints with additional network rules, ensuring only authorized IPs can initiate connections. For example, a company might restrict access to its office VPN range, blocking all other traffic. ACLs work at the database level, complementing VCN security.
The incorrect options are:
Security List (A): Security Lists operate at the VCN subnet level, controlling traffic to all resources in the subnet (e.g., ingress TCP 1522 to an ADB subnet). While useful, they're broader than ADB-specific ACLs, which target the database instance directly, making ACLs the precise answer here.
IP Vault (B): There's no "IP Vault" in OCI. This might confuse OCI Vault (for secrets), but it doesn't manage IP access.
IPSec List (D): IPSec secures traffic via VPNs, not IP allowlisting for database access. It's unrelated to ADB connectivity restrictions.
ACLs provide a database-specific, user-friendly way to enforce IP-based access control.

NEW QUESTION # 18
Autonomous Database's auto scaling feature allows your database to use up to three times the current base number of OCPU cores at any time. As demand increases, auto scaling automatically increases the number of cores in use. Likewise, as demand drops, auto scaling automatically decreases the number of cores in use. Which statement is FALSE regarding the auto scaling feature?

A. The base number of OCPU cores allocated to a database is not guaranteed.
B. For databases on dedicated Exadata infrastructure, the maximum number of cores is limited by the number of free cores that are not being used by other auto scaling databases to meet high-load demands.
C. For databases on dedicated Exadata infrastructure, the maximum number of cores available to a database depends on the total number of cores available in the Exadata infrastructure instance.
D. Auto Scaling is enabled by default and can be enabled or disabled at any time.

Answer: A

Explanation:
Auto scaling in Autonomous Database dynamically adjusts OCPU usage up to three times the base allocation. Let's evaluate each statement:
Correct Answer (C): "The base number of OCPU cores allocated to a database is not guaranteed" is false. The base OCPU count, set during provisioning or manual scaling, is always guaranteed as the minimum available resource, even with auto scaling enabled. Auto scaling only increases usage above this baseline when needed.
True Statements:
A: On dedicated Exadata, the max cores for auto scaling are constrained by available free cores not used by other databases, ensuring resource fairness.
B: The total cores in the Exadata instance define the upper limit for any database's auto scaling capacity.
D: Auto scaling is not enabled by default (must be explicitly activated) and can be toggled on/off, though this statement's phrasing could be clearer-it's still true in context.
This guarantees predictable minimum performance while allowing flexibility for peak loads.

NEW QUESTION # 19
Which workload is particularly suited to Oracle Autonomous JSON Database?

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

Answer: C

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 # 20
Which statement is FALSE about loading data into the Autonomous Database using the Data Load card in Database Actions?

A. You must first manually create your database credentials using DBMS_CLOUD.CREATE_CREDENTIAL before accessing your Oracle Object Storage Bucket
B. Data can be uploaded from several cloud storage sources including S3, Azure, Google Cloud, and Oracle Object Storage
C. Data can be loaded from a local data source
D. Data can be loaded from a remote database using Database Links (DBLinks)
E. Data formats supported include: text, CSV, JSON, Avro, and Parquet

Answer: A

Explanation:
The Data Load card in Database Actions (within ADB's web interface) simplifies data loading. The false statement is:
You must first manually create your database credentials using DBMS_CLOUD.CREATE_CREDENTIAL before accessing your Oracle Object Storage Bucket (D): This is incorrect. The Data Load card automates credential management for Oracle Object Storage by leveraging the ADB instance's IAM permissions. When you select an OCI Object Storage bucket in the UI, it uses the instance's resource principal or user OCI credentials (e.g., from your signed-in OCI session), eliminating the need to manually run DBMS_CLOUD.CREATE_CREDENTIAL. For example, uploading sales.csv from a bucket via the Data Load card requires only bucket selection and file mapping-no PL/SQL credential setup. This automation enhances usability, contrasting with manual methods where CREATE_CREDENTIAL is needed (e.g., in SQL scripts).
The true statements are:
Data formats supported include: text, CSV, JSON, Avro, and Parquet (A): The Data Load card supports these formats, parsing them into tables using DBMS_CLOUD under the hood. E.g., a JSON file { "id": 1, "name": "John" } loads as rows.
Data can be loaded from a local data source (B): You can upload files directly from your local machine (e.g., a CSV on your desktop) via the browser interface, staging them temporarily for loading.
Data can be uploaded from several cloud storage sources including S3, Azure, Google Cloud, and Oracle Object Storage (C): The card supports these external cloud sources, requiring credentials (e.g., AWS keys), alongside native OCI Object Storage integration.
Data can be loaded from a remote database using Database Links (E): DBLinks allow pulling data from another Oracle database (e.g., INSERT INTO local_table SELECT * FROM remote_table@link), supported in the Data Load card.
The automation of credentials in D is a key differentiator for the UI-based Data Load feature.

NEW QUESTION # 21
Which management operation is correct about Autonomous Databases on Shared Exadata Infrastructure?

A. You cannot configure the scheduling for your Autonomous Databases on Shared Exadata Infrastructure
B. You can skip a scheduled maintenance run. For Autonomous Database on Shared Exadata Infrastructure, you can skip maintenance runs for up to two consecutive quarters if needed
C. You can choose to use Release Update or Release Update Revision updates for your Autonomous Databases on Shared Infrastructure
D. You can perform a "rolling restart" on all the Autonomous Databases. During a rolling restart, each node on the Autonomous Database is restarted separately while the remaining nodes continue to be available

Answer: A

Explanation:
Management operations for Autonomous Databases on Shared Exadata Infrastructure are limited due to its fully managed nature. The correct statement is:
You cannot configure the scheduling for your Autonomous Databases on Shared Exadata Infrastructure (C): In shared infrastructure, Oracle fully controls maintenance scheduling (e.g., patching, upgrades). Unlike dedicated infrastructure, where users can set maintenance windows, shared ADB users cannot adjust timing. Oracle notifies users of upcoming maintenance (e.g., via email or console), typically in a 7-day window, but the exact schedule is Oracle-driven to optimize the shared Exadata platform. For example, a quarterly patch might occur on a Tuesday at 2 AM UTC, and users must adapt, not reschedule.
The incorrect options are:
You can skip a scheduled maintenance run... (A): False. Shared infrastructure does not allow skipping maintenance runs, even for two quarters. This flexibility exists only in dedicated infrastructure, where users have more control (e.g., skipping up to two consecutive updates). In shared mode, Oracle enforces updates for security and stability across all tenants.
You can perform a "rolling restart"... (B): False. Rolling restarts (restarting nodes sequentially for availability) are not user-initiated in ADB shared infrastructure. Restarts, if needed, are managed by Oracle during maintenance, and users cannot control the process or ensure node-by-node availability.
You can choose to use Release Update or Release Update Revision updates... (D): False. In shared infrastructure, Oracle applies Release Updates (RUs) uniformly across all databases; users cannot choose between RU or Release Update Revisions (RURs), a feature reserved for dedicated deployments.
This reflects the trade-off of shared infrastructure: lower cost and management effort for less control.

NEW QUESTION # 22
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