Oracle 1z0-931-25 - Oracle Autonomous Database Cloud 2025 Professional

Full Detailed In-Depth Explanation:

Bring Your Own License (BYOL) allows using existing on-premises Oracle licenses in the cloud:

A:False. Exadata is included in Autonomous Database; no separate license is needed.

B:False. Active Data Guard is an optional feature, not required for BYOL.

C:True. RAC is needed for BYOL when scaling beyond 16 OCPUs, as Autonomous Database uses RAC for high availability in larger deployments.

D:True. Multitenant is mandatory, as Autonomous Database uses a multitenant architecture (CDB/PDB).

E:False. TDE is included by default, not a BYOL requirement.

Full Detailed In-Depth Explanation:

Autonomous Transaction Processing (ATP) offers predefined service levels with varying concurrency and parallelism capabilities:

MEDIUM:Supports up to 50 concurrent statements per OCPU, with no parallelism by default. Unsuitable for the requirement.

TPURGENT:Supports up to 200 concurrent statements per OCPU and enables manual parallelism. This meets both requirements (concurrency ≥ 200 and parallelism), making it the correct choice.

LOW:Supports only 25 concurrent statements per OCPU, with no parallelism. Insufficient for the requirement.

TP:Supports 125 concurrent statements per OCPU, with no parallelism by default. Falls short of the 200 concurrency threshold.

TPURGENT is designed for high-concurrency, time-sensitive workloads, providing the necessary resources and flexibility for parallel query execution, aligning perfectly with the specified needs.

Autonomous Transaction Processing (ATP) provides predefined connection services to optimize different workload types. For a high-concurrency OLTP application with parallel reporting queries, the appropriate service is:

HIGH (C):The HIGH connection service in ATP is designed for workloads requiring high concurrency and throughput, making it ideal for a production OLTP application like "EXAM" that handles many simultaneous transactions (e.g., user requests). Additionally, HIGH supports parallel query execution, which is critical for running reporting queries efficiently during off-peak times. It allocates more resources (e.g., OCPUs and I/O) compared to other services, ensuring performance for both transactional and analytical tasks. For example, the OLTP app might use HIGH to process thousands of concurrent user requests, while a nightly report leverages parallel processing to aggregate data quickly. In the wallet’s tnsnames.ora, the HIGH service might look like exam_high = (DESCRIPTION=...), offering the best balance for this mixed workload.

The incorrect options are:

TPURGENT (A):The TPURGENT service prioritizes low-latency, time-critical transactions (e.g., sub-second response times for single-user actions). It’s optimized for latency-sensitive operations, not high concurrency or parallel reporting, and would underperform for the broader OLTP and reporting needs here. For instance, it’s better suited for a single critical transaction than a multi-user system.

TP (B):The TP (Transaction Processing) service is a general-purpose option for OLTP workloads, offering moderate concurrency and latency. However, it’s not optimized for high concurrency or parallel query execution, making it less suitable for a production app with reporting demands. It’s a middle ground, not a top-tier performer like HIGH.

MEDIUM (D):The MEDIUM service balances performance and resource usage for moderate workloads. It supports some concurrency but lacks the resource allocation and parallel execution capabilities of HIGH, making it inadequate for a high-concurrency OLTP system with reporting requirements.

The HIGH service’s ability to handle both high transactional volume and parallel reporting aligns perfectly with the scenario’s strict performance needs, all within ATP’s zero-maintenance framework.

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.

Autonomous Database allows independent scaling of certain resources:

Correct Answer (B): “Storage” can be scaled independently of OCPUs via the OCI Console or API, adjusting capacity (e.g., from 1 TB to 2 TB) without altering compute resources.

Incorrect Options:

A: Sessions depend on CPU and memory limits, not independently scalable.

C: Memory scales with OCPUs in a fixed ratio, not separately.

Defining a maintenance schedule for Dedicated Exadata Infrastructure allows customization:

Correct Answer (B): “Month of the Quarter, Week of the Month, Day of the Week, Start Hour” is the correct set. For example, you can specify “Month 2 of Q1, Week 3, Wednesday, 02:00 AM,” aligning with quarterly planning while offering weekly and daily precision.

Incorrect Options:

A: “Quarter of the Year” and “Date of the Month” are less flexible than week-based options and not the standard format.

C: “Month of the Year” skips the quarterly structure used in dedicated maintenance.

Oracle Data Pump is a powerful tool for migrating databases to Autonomous Database (ADB). The two correct advantages are:

Data Pump can exclude migration of objects like indexes and materialized views that are not needed by Autonomous Database (C):True. Data Pump’s EXCLUDE parameter allows skipping objects like indexes and materialized views during export (e.g., expdp ... EXCLUDE=INDEX,MATERIALIZED_VIEW). In ADB, these objects are often redundantbecause the database automatically creates and manages them based on workload (e.g., auto-indexing). For example, exporting a schema with EXCLUDE=INDEX from an on-premises database reduces migration overhead, as ADB recreates necessary indexes post-import, optimizing for its managed environment. This flexibility minimizes unnecessary data transfer and speeds up the process.

Data Pump is platform-independent - it can migrate Oracle databases running on any platform (D):True. Data Pump uses a platform-agnostic dump file format (.dmp), enabling migration from any Oracle Database (e.g., on Linux, Windows, or Solaris) to ADB in the cloud. For instance, you could export from an Oracle 12c database on AIX, upload the dump to OCI Object Storage, and import it into ADB using DBMS_CLOUD.COPY_DATA, regardless of endianness or OS differences (handled by Data Pump’s conversion). This universality makes it ideal for heterogeneous migrations.

The incorrect options are:

Data Pump is faster to migrate database than using RMAN (A):False. Speed depends on context—RMAN (Recovery Manager) is faster for physical migrations (e.g., restoring backups) of entire databases, especially large ones, due to block-level copying. Data Pump, a logical migration tool, extracts and loads data row-by-row, which can be slower for massive datasets but offers more control (e.g., schema selection). No universal speed advantage exists; it’s workload-specific.

Data Pump creates the tablespaces used by your Autonomous Database (B):False. In ADB, tablespaces are fully managed by Oracle (e.g., DATA tablespace), and Data Pump doesn’t create them. It imports data into existing, pre-allocated storage, ignoring source tablespace definitions. E.g., a source tablespace USERS is mapped to ADB’s default storage, not recreated.

These advantages make Data Pump a versatile, tailored migration solution for ADB.

Autonomous Data Warehouse (ADW) uses consumer groups (High, Medium, Low) to manage resource allocation:

Correct Answer (A): “Low provides highest concurrency and lowest resources, and DoP is 1” is true. The Low group is designed for many lightweight, short-running queries, offering maximum concurrent sessions but minimal CPU/memory per session, with a Degree of Parallelism (DoP) of 1 (serial execution).

Incorrect Options:

B: High prioritizes resources, not concurrency; it has fewer sessions with more power.

C: Medium offers balanced resources and concurrency; queries can run in parallel (DoP > 1), not just serially.

Graph Studio in Autonomous Database enables graph creation and analysis:

Correct Answer (A): “Tables in an Autonomous Database instance” are used to create graphs. Graph Studio builds property graphs from relational tables by defining vertices (nodes) and edges (relationships) based on existing data, leveraging the database’s schema.

Incorrect Options:

B: Graph analytics algorithms analyze existing graphs, not create them.

C: NoSQL configuration is unrelated; Graph Studio uses relational data.

D: No external tool from oracle.com is required; Graph Studio is a built-in feature.

Full Detailed In-Depth Explanation:

The Service Console is a database-specific management interface:

A:False. Auto-scaling is managed via the OCI Console, not the Service Console.

B:True. The Service Console allows monitoring and terminating runaway SQL statements that consume excessive resources.

C:False. Manual backups are created through OCI Console or SQL commands, not the Service Console.

D:False. Moving compartments is an OCI Console function, not a Service Console task.