SIMULATE THE REAL EXAM WITH ORACLE 1Z0-931-25 PRACTICE EXAMS

Simulate the Real Exam with Oracle 1Z0-931-25 Practice Exams

Simulate the Real Exam with Oracle 1Z0-931-25 Practice Exams

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Oracle 1Z0-931-25 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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 3
  • 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 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
  • 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 7
  • 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.

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Oracle Autonomous Database Cloud 2025 Professional Sample Questions (Q15-Q20):

NEW QUESTION # 15
Which two optimizations are different between Autonomous Data Warehouse and Autonomous Transaction Processing? (Choose two.)

  • A. Data Organization
  • B. Backup Retention
  • C. Undo Management
  • D. Memory Usage

Answer: A,D

Explanation:
Autonomous Data Warehouse (ADW) and Autonomous Transaction Processing (ATP) are optimized for different workloads, reflected in their configurations. The two differing optimizations are:
Memory Usage (A): ADW and ATP allocate memory differently to suit their purposes. ADW prioritizes a larger data cache (part of the SGA) to keep more data in memory, boosting analytical query performance (e.g., aggregations over millions of rows). For example, a SELECT SUM(sales) GROUP BY region runs faster with more cached data. ATP, conversely, balances memory across the SGA and PGA for transactional workloads, emphasizing concurrency and quick row-level operations (e.g., UPDATE orders SET status = 'shipped'). This difference ensures ADW excels at scan-heavy analytics, while ATP handles high-throughput updates.
Data Organization (B): ADW uses a columnar storage format (e.g., Hybrid Columnar Compression) optimized for analytics, storing data by column to speed up aggregations and reduce I/O (e.g., scanning only the sales column for a SUM). ATP uses a row-based format suited for OLTP, enabling fast single-row access and updates (e.g., retrieving or modifying a specific order_id). For instance, inserting a row in ATP is efficient due to row storage, while ADW's columnar format accelerates SELECT AVG(price) FROM products.
The incorrect options are:
Backup Retention (C): Both ADW and ATP use the same automatic backup system (via Oracle's Automatic Workload Repository), with a default 60-day retention adjustable by users. There's no optimization difference here; it's a shared managed feature.
Undo Management (D): Both databases use Oracle's Flashback technology for undo (e.g., rolling back transactions or querying past states), with retention periods set similarly. Undo is managed automatically in both, not optimized differently.
These optimizations tailor ADW for analytics and ATP for transactions, despite their shared autonomous foundation.


NEW QUESTION # 16
Oracle Data Safe is a unified control center for your Oracle databases which helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements. Which statement is FALSE for Oracle Data Safe?

  • A. Oracle Data Safe helps you find sensitive data in your database by inspecting the actual data in your database and its data dictionary
  • B. Oracle Data Safe only supports Autonomous Database
  • C. Oracle Data Safe helps you assess the security of your cloud database configurations by analyzing database configurations
  • D. Oracle Data Safe evaluates user types, how users are authenticated, and the password policies assigned to each user

Answer: B

Explanation:
Oracle Data Safe enhances database security across various Oracle environments. The false statement is:
Oracle Data Safe only supports Autonomous Database (D): This is incorrect. Oracle Data Safe supports a wide range of Oracle databases, not just Autonomous Database. It works with Autonomous Database (shared and dedicated), Oracle Database Cloud Service (VM and Bare Metal), Exadata DB Systems, on-premises Oracle Databases, and Oracle Database on OCI Compute. For example, a DBA could use Data Safe to mask sensitive data in an on-premises 19c database or assess security in an Exadata Cloud@Customer deployment, not just ADB. This broad compatibility makes it a unified security tool across Oracle's ecosystem.
The true statements are:
Oracle Data Safe helps you find sensitive data in your database by inspecting the actual data in your database and its data dictionary (A): Data Safe's Data Discovery feature scans tables and metadata to identify sensitive columns (e.g., SSNs, credit card numbers), using predefined and custom patterns.
Oracle Data Safe helps you assess the security of your cloud database configurations by analyzing database configurations (B): The Security Assessment feature evaluates settings like encryption, auditing, and privileges, providing risk scores and recommendations.
Oracle Data Safe evaluates user types, how users are authenticated, and the password policies assigned to each user (C): User Assessment analyzes user accounts, authentication methods (e.g., password, SSO), and policies, highlighting risks like weak passwords.
The misconception in D limits Data Safe's scope, which extends beyond ADB to all supported Oracle databases.


NEW QUESTION # 17
Which subset of services is offered via OCI-CLI (Command Line Interface) for Autonomous Database (ADB) via calls made to the OCI APIs?

  • A. Create, Query, Update, List, Start
  • B. Start, Delete, Update, Query, Stop
  • C. Create, Query, List, Stop, Restore
  • D. Create, Get, List, Stop, Restore

Answer: D

Explanation:
The OCI Command Line Interface (CLI) provides a range of commands for managing Autonomous Database via OCI APIs. The correct answer is:
Create, Get, List, Stop, Restore (B): These are key operations supported by the OCI CLI for Autonomous Database:
Create: oci db autonomous-database create provisions a new ADB instance.
Get: oci db autonomous-database get retrieves details of a specific ADB.
List: oci db autonomous-database list lists all ADBs in a compartment.
Stop: oci db autonomous-database stop halts the database.
Restore: oci db autonomous-database restore restores from a backup.
The incorrect options are:
A (Start, Delete, Update, Query, Stop): "Query" is not a CLI command; "Delete" and "Update" are valid but not part of this specific subset.
C (Create, Query, Update, List, Start): "Query" is invalid; "Update" is supported but not listed here.
D (Create, Query, List, Stop, Restore): "Query" is not a valid CLI operation.
This subset reflects common management tasks via CLI.


NEW QUESTION # 18
Which two statements are true about Data Insights?

  • A. Data Insights is available with on-premises deployments of Oracle Database.
  • B. You can retrieve previously executed Data Insights searches.
  • C. You can search for Data Insights against a base table or business model.
  • D. Data Insights is an additional priced option.

Answer: B,C

Explanation:
Full Detailed In-Depth Explanation:
A: True. Data Insights works with tables and business models in ADW.
B: False. Exclusive to Autonomous Database, not on-premises.
C: True. Search history is retrievable.
D: False. Included in ADW, not separately priced.


NEW QUESTION # 19
Which two statements are correct about Autonomous Data Warehouse on Shared Exadata Infrastructure?

  • A. Parallelism is not enabled by default.
  • B. Compression is enabled by default. Autonomous Data Warehouse uses Hybrid Columnar Compression for all tables by default.
  • C. You have direct access to the database node.
  • D. Oracle Database Result Cache is enabled by default for all SQL statements.

Answer: B,D

Explanation:
Let's evaluate each statement about Autonomous Data Warehouse (ADW) on Shared Exadata Infrastructure:
A . Oracle Database Result Cache is enabled by default for all SQL statements: True. ADW enables the Result Cache by default to improve query performance by storing frequently accessed results in memory.
B . You have direct access to the database node: False. ADW is a fully managed service; users do not have direct access to underlying nodes, which Oracle manages for patching, scaling, and security.
C . Parallelism is not enabled by default: False. Parallelism is enabled by default in ADW to optimize large analytical queries across multiple CPUs.
D . Compression is enabled by default. Autonomous Data Warehouse uses Hybrid Columnar Compression for all tables by default: True. Hybrid Columnar Compression (HCC) is applied automatically to reduce storage and enhance query performance.
Thus, A and D are correct, reflecting ADW's default performance optimizations.


NEW QUESTION # 20
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