Free Oracle 1z0-931-25 Practice Exam with Questions & Answers | Set: 2

When designing access controls for an Autonomous Dedicated environment, Oracle recommends redundancy and separation for security and manageability:

Correct Answer (D): “Create at least 2 of each resource” (subnets, compartments, user groups) is a best practice:

Subnets: Using at least two subnets (e.g., one public, one private) enhances security by segregating traffic and provides failover options if one subnet encounters issues.

Compartments: Multiple compartments allow logical separation (e.g., dev, test, prod), simplifying access control and resource management.

User Groups: At least two groups (e.g., admins, developers) streamline permission assignments and reduce the risk of over-privileging users.

Incorrect Options:

A: OCI allows multiple subnets and compartments; restricting to one limits flexibility and security.

B: There’s no such limitation; multiple resources are supported and encouraged.

Scaling resources in Autonomous Database offers flexibility. The true statement is:

OCPUs and storage can be scaled independently (A):In Autonomous Database, you can adjust the number of OCPUs (compute resources) and storage capacity (in terabytes) separately via the OCI console or CLI. For example, you might provision an ADB with 2 OCPUs and 1 TB of storage. Later, you could scale to 4 OCPUs without changing storage, or increase storage to 2 TB without touching OCPUs. This decoupling allows tailored resource allocation—e.g., more compute for a CPU-intensive workload or more storage for growing data—without over-provisioning. Scaling is online, with no downtime, and status shows “SCALING IN PROGRESS” during the operation.

The incorrect options are:

Use auto scaling to increase storage (B):Auto scaling applies to OCPUs only, allowing up to 3x the base CPU allocation dynamically. Storage scaling is manual; you specify a new size (e.g., via oci db autonomous-database update), not via auto scaling.

Increasing OCPUs will automatically increase storage (C):There’s no automatic linkage between OCPU and storage scaling. They are independent parameters, and increasing one does not affect the other unless explicitly requested.

OCPUs and storage must remain in sync (D):No such synchronization is required. You can have 1 OCPU with 10 TB or 10 OCPUs with 1 TB, depending on workload needs.

This independence is a hallmark of Autonomous Database’s elasticity.

Full Detailed In-Depth Explanation:

Autonomous Transaction Processing (ATP) supports specific service names for connectivity:

TPURGENT:High-priority service with 200 concurrent statements per OCPU and parallelism.

MEDIUM:Balanced service for moderate workloads.

HIGH:Optimized for reporting/batch jobs with high parallelism.

LOW:Low-priority service for minimal resource use.

TP:General-purpose transactional service.

TPPERFORMANTis not a recognized service name in ATP documentation, making A the correct answer.

The scenario requires a low-maintenance, high-performance database for an OLTP web application with occasional reporting. The correct answer is:

ATP using 'tpurgent' and 'high' TNS services to separate connection types (A):Autonomous Transaction Processing (ATP) is ideal here. It’s a fully managed database optimized for OLTP workloads (e.g., scheduling service requests) with zero maintenance overhead—Oracle handles patching, backups, and tuning. ATP supports multiple connection services:

'tpurgent':Prioritizes low-latency, time-critical transactions (e.g., customer scheduling requests), ensuring fast response times for the web app.

'high':Suited for high-concurrency or reporting queries, allowing operational reports to run during non-peak hours without impacting the OLTP workload.By using these predefined services, the architecture separates transactional and reporting workloads within the same database, meeting performance needs without additional administration. For example, the web app connects via tpurgent for real-time updates, while a reporting tool uses high for batch queries at night, leveraging ATP’s auto-scaling if needed.

The incorrect options are:

Since the application needs to be highly available, it should be deployed on a Kubernetes Cluster (B):This misinterprets the question—it’s about the database service,not the application deployment. Kubernetes is for container orchestration, not a database solution, and adds complexity counter to the low-maintenance goal.

It is best to build a separate data warehouse, and move the OLTP data on a nightly basis (C):While a separate Autonomous Data Warehouse (ADW) could handle reporting, it requires data movement (e.g., via ETL), increasing admin effort and complexity, which the DBA Manager wants to avoid. ATP can handle both workloads with proper service separation.

ADW since operational reporting is a higher priority in this scenario (D):ADW is optimized for analytics, not OLTP. The web app’s transactional needs are primary, with reporting secondary and occasional, making ATP more suitable.

ATP’s self-managing nature and service flexibility make it the best fit.

Autonomous Database provides predefined roles tailored to specific use cases. The correct answeris:

DWROLE (B):The DWROLE predefined role is designed for Data Warehouse developers. It includes privileges commonly needed for data warehousing tasks, such as creating tables, views, and materialized views, as well as executing analytical queries. This role is optimized for Autonomous Data Warehouse (ADW) workloads.

The incorrect options are:

ADBDEV (A):There is no predefined ADBDEV role in Autonomous Database; this appears to be a fictional or misinterpreted role.

ADMIN (C):The ADMIN role is a superuser role with full database privileges, far exceeding the needs of a typical Data Warehouse developer and not tailored to that specific use case.

ADWC (D):This is not a predefined role; it might be a typo or confusion with ADW (Autonomous Data Warehouse), but no such role exists.

DWROLE is the best fit for a Data Warehouse developer’s needs.

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.

Enabling a new business analyst to use SQL Developer Web with Autonomous Database requires specific steps. The correct answer is:

Create a database user (with connect, resource, object privileges), enable the schema to use SQL Developer Web, and provide the user with the user-specific modified URL (C):

Create a database user:As the ADMIN user, create a new database user (e.g., ANALYST1) with CONNECT (to log in), RESOURCE (to create objects), and object-specific privileges (e.g., SELECT on target tables). Example: CREATE USER ANALYST1 IDENTIFIED BY "password"; GRANT CONNECT, RESOURCE TO ANALYST1; GRANT SELECT ON HR.EMPLOYEES TO ANALYST1;. This ensures the analyst can access and query tables.

Enable the schema for SQL Developer Web:Use the ORDS_ADMIN.ENABLE_SCHEMA procedure to activate the schema for web access. Example: EXEC ORDS_ADMIN.ENABLE_SCHEMA(p_schema => 'ANALYST1');. This step integrates the user with Oracle REST Data Services (ORDS), which powers SQL Developer Web in ADB.

Provide the user-specific URL:After enabling the schema, generate and share the SQL Developer Web URL, which includes the user’s credentials (e.g., https:// <adb-host>/ords/analyst1/_sdw). The analyst logs in with their database username and password, accessing a browser-based SQL interface to explore tables.

The incorrect options are:

Create a database user with connect, resource, and object privileges (A):This alone isn’t enough; without enabling the schema for SQL Developer Web, the user can’t access it via the web interface.

Create a database user with the default privileges (B):Default privileges (e.g., just CONNECT) are insufficient for table access or web use; specific grants and ORDS setup are needed.

Create an IDCS user, create a database user with connect, resource, and object privileges (D):Oracle Identity Cloud Service (IDCS) integration is optional and not required for basic SQL Developer Web access in ADB. It’s overkill unless SSO is mandated, which isn’t specified here.

This multi-step process ensures secure, web-based access tailored to the analyst’s needs.

Application Continuity ensures seamless failover for applications:

Correct Answer (B): EXEC DBMS_CLOUD_ADMIN.ENABLE_APP_CONT(''); is the correct command for Autonomous Database on Shared Infrastructure. It enables Application Continuity for a specific service (e.g., tpurgent), leveraging the DBMS_CLOUD_ADMIN package designed for cloud-specific administration.

Incorrect Options:

A: ALTER SESSION only affects the current session, not persistent database-wide settings.

Full Detailed In-Depth Explanation:

When provisioning an Autonomous Container Database (ACD) on dedicated infrastructure, Oracle provides specific options for backup retention periods to balance data recovery needs with storage costs. According to the official Oracle documentation, the available backup retention periods for a dedicated ACD are:

7 days: This is the default retention period for a newly provisioned ACD.

15 days: An option for extended retention beyond the default.

60 days: The maximum supported retention period for ACDs, offering the longest recovery window.

The option of120 daysis not supported as a backup retention period for an Autonomous Container Database. This limitation is due to the design of the Autonomous Database service, which caps retention at 60 days to optimize storage and performance on dedicated Exadata infrastructure. Attempting to set a retention period beyond 60 days is not an available choice during provisioning. Users must select a retention period that meets their recovery point objectives (RPO) within these constraints, noting that longer retention increases storage usage and associated costs.

Addressing a storage I/O bottleneck for insert throughput in Autonomous Database involves resource adjustments:

Correct Answer (C): “Increase the number of OCPUs allocated to the database” boosts processing power, which directly improves I/O performance. In Autonomous Database, OCPUs handle both compute and I/O operations; more OCPUs increase the I/O bandwidth, reducing the bottleneck for insert-heavy workloads.

Incorrect Options:

A: Removing non-JSON data may optimize storage use but doesn’t directly addressI/O throughput for inserts.

B: “Noisy neighbors” is a shared infrastructure concern, but migration isn’t a standard solution for I/O bottlenecks and requires Oracle intervention, not user control.