ORACLE 1Z0-931-25 RELIABLE STUDY NOTES - CERTIFICATION 1Z0-931-25 TEST ANSWERS

Oracle 1Z0-931-25 Reliable Study Notes - Certification 1Z0-931-25 Test Answers

Oracle 1Z0-931-25 Reliable Study Notes - Certification 1Z0-931-25 Test Answers

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Tags: 1Z0-931-25 Reliable Study Notes, Certification 1Z0-931-25 Test Answers, Reliable 1Z0-931-25 Exam Syllabus, Exam 1Z0-931-25 Simulations, 1Z0-931-25 Related Certifications

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Oracle 1Z0-931-25 Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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 4
  • 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.

>> Oracle 1Z0-931-25 Reliable Study Notes <<

Certification 1Z0-931-25 Test Answers & Reliable 1Z0-931-25 Exam Syllabus

The NewPassLeader wants to help students ace the certification exam preparation. To achieve this goal the NewPassLeader is offering real, valid, and updated exam questions in three different formats. These Oracle 1Z0-931-25 exam questions formats are PDF file, desktop practice test software, and web-based practice test software. All these three 1Z0-931-25 Exam Practice question formats are easy to use. The 1Z0-931-25 desktop practice test software and web-based practice test software both are the easy-to-use mock Oracle Autonomous Database Cloud 2025 Professional (1Z0-931-25) exam. These 1Z0-931-25 mock exams are designed to simulate the conditions of a real exam.

Oracle Autonomous Database Cloud 2025 Professional Sample Questions (Q121-Q126):

NEW QUESTION # 121
Which two optimizations are different between Autonomous Data Warehouse and Autonomous Transaction Processing? (Choose two.)

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

Answer: B,C

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 # 122
Where are the customer-managed encryption keys stored for Autonomous Database on Dedicated Infrastructure?

  • A. Inside the backup of the container database
  • B. Inside the Autonomous Database wallet
  • C. On the Exadata infrastructure where the Autonomous Database Dedicated is hosted
  • D. In a separate key vault external to the Exadata infrastructure

Answer: D

Explanation:
Customer-managed encryption keys enhance security control:
Correct Answer (A): "In a separate key vault external to the Exadata infrastructure" refers to OCI Vault (Key Management Service), where keys are securely stored and managed outside the database infrastructure.
Incorrect Options:
B: The wallet secures connections, not encryption keys.
C: Storing keys on Exadata compromises separation of duties.
D: Backups don't store keys; they're encrypted by keys from the vault.
This separation ensures robust key management.


NEW QUESTION # 123
What are three characteristics of Data Lake data captured in Object Storage? (Choose three.)

  • A. High concurrency
  • B. Schema on read
  • C. Multiple subject areas
  • D. High transaction performance
  • E. Mixed data types

Answer: B,C,E

Explanation:
Data Lakes in OCI Object Storage store raw data for analysis. The three correct characteristics are:
Schema on read (C): Data Lakes store data in its raw, native format (e.g., JSON, CSV, Parquet) without a predefined schema. The schema is applied when data is read or processed, not when written, offering flexibility. For example, a Parquet file with sales data might be queried with SQL only when analyzed, not structured upfront like in a database.
Multiple subject areas (D): Data Lakes aggregate data from diverse sources-sales, HR, IoT-spanning multiple subject areas. This enables cross-domain analysis, like combining customer data with weather data for insights, all stored in a single OCI bucket.
Mixed data types (E): Data Lakes support varied formats: structured (e.g., CSV tables), semi-structured (e.g., JSON documents), and unstructured (e.g., videos). For instance, a bucket might hold CSV logs, JSON events, and image files, all accessible for processing.
The incorrect options are:
High concurrency (A): Data Lakes in Object Storage are not designed for high-concurrency transactional access (e.g., thousands of simultaneous updates). They're optimized for batch processing or analytics, unlike ATP's concurrency focus.
High transaction performance (B): Transactional performance (e.g., fast commits) is a database strength, not a Data Lake's. Object Storage prioritizes scalability and durability over transactional speed, making it unsuitable for OLTP workloads.
These traits make Data Lakes ideal for big data analytics, not real-time transactions.


NEW QUESTION # 124
Which statement is true about the use of Access Control Lists (ACLs) with an Autonomous Database on Shared Infrastructure?

  • A. When you restore a database, the existing ACLs are not overwritten by the restore.
  • B. An ACL can be set up for an IP Address or a virtual cloud network but not both at the same time
  • C. ACLs can only be used with private endpoints
  • D. An ACL can only be set during the creation of an Autonomous Database on Shared Infrastructure

Answer: A

Explanation:
ACLs control network access to Autonomous Database on Shared Infrastructure:
Correct Answer (B): "When you restore a database, the existing ACLs are not overwritten by the restore" is true. ACLs are part of the database's network configuration, preserved during restore operations to maintain security settings.
Incorrect Options:
A: ACLs can include both IP addresses and VCN CIDR blocks simultaneously; they're not mutually exclusive.
C: ACLs apply to public endpoints, not just private ones, to restrict access.
D: ACLs can be modified post-creation, not just at provisioning time.
This ensures consistent security post-restore.


NEW QUESTION # 125
Which two statements are true regarding active transactions when scaling OCPUs in an Autonomous Database? (Choose two.)

  • A. Active transactions continue running unaffected
  • B. Scaling can happen while there are active transactions in the database
  • C. Active transactions are terminated and rolled back
  • D. Active transactions are paused

Answer: A,B

Explanation:
Scaling OCPUs in Autonomous Database is designed to be seamless. The two true statements are:
Scaling can happen while there are active transactions in the database (B): ADB supports online scaling, meaning you can increase or decrease OCPUs (e.g., from 2 to 4) via the OCI console or CLI (e.g., oci db autonomous-database update --cpu-core-count 4) without stopping the database. Active transactions (e.g., INSERT INTO orders VALUES (...)) continue running during this process. Oracle's architecture ensures the database remains available, adjusting resources in the background. For example, a web app processing orders won't notice the scaling operation starting at 10:00 AM.
Active transactions continue running unaffected (C): During scaling, existing transactions are not interrupted, terminated, or paused. They complete normally, with Oracle managing resource allocation transparently (e.g., shifting CPU usage without killing sessions). For instance, a long-running UPDATE statement started before scaling finishes successfully, leveraging the database's high-availability design. The status shows "SCALING IN PROGRESS," but users experience no downtime.
The incorrect options are:
Active transactions are terminated and rolled back (A): False. Scaling is non-disruptive; transactions aren't killed or rolled back, preserving data integrity and user experience. Termination only occurs during explicit stops or failures, not scaling.
Active transactions are paused (D): False. There's no pausing mechanism during scaling; transactions run continuously, as pausing would disrupt OLTP or analytical workloads, countering ADB's autonomous promise.
This online scaling capability is a key benefit, ensuring uninterrupted service.


NEW QUESTION # 126
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