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Oracle 1Z0-931-25 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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 4

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 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

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 (Q87-Q92):

NEW QUESTION # 87
Which three options do NOT change when enabling auto scaling? (Choose three.)

A. Amount of storage
B. I/O resources
C. Level of concurrency
D. Number of OCPUs displayed in the console
E. Parallelism settings

Answer: A,C,E

Explanation:
When enabling auto scaling in an Oracle Autonomous Database, the feature dynamically adjusts resources based on workload demand, but certain configuration elements remain unchanged unless manually altered.
Amount of storage (A): Auto scaling focuses on adjusting CPU and I/O resources to meet performance needs. The storage allocation remains constant because it is a separately provisioned resource that requires manual adjustment via the OCI Console or API. This ensures that storage capacity is not inadvertently reduced or expanded without explicit user intent.
Parallelism settings (B): These settings determine how many parallel processes are used for query execution. Auto scaling does not modify this pre-defined configuration; it adjusts resource usage (e.g., CPU cores) without altering the parallelism framework established for the database.
Level of concurrency (E): Concurrency refers to the maximum number of simultaneous user sessions. While auto scaling can indirectly influence concurrency by adjusting available resources, the concurrency limit itself is a fixed setting that remains unchanged unless explicitly modified by the administrator.
Incorrect Options:
I/O resources (C): Auto scaling directly impacts I/O resources by increasing or decreasing them alongside CPU adjustments to handle workload fluctuations.
Number of OCPUs displayed in the console (D): While the base OCPU count remains static, the effective number of OCPUs in use (up to three times the base) changes dynamically with auto scaling, and this is reflected in the console, making this option subject to change.
This behavior ensures that auto scaling optimizes performance without disrupting foundational database configurations.

NEW QUESTION # 88
Which two objects are imported when using Data Pump to migrate your Oracle database to Autonomous Database? (Choose two.)

A. Data
B. Tablespaces
C. Schemas
D. Report

Answer: A,C

Explanation:
Oracle Data Pump is a key tool for migrating databases to Autonomous Database. The two objects imported are:
Data (B): Data Pump imports the actual data from the source database into the target Autonomous Database. This includes rows from tables, LOBs, and other data types stored in the dump file (e.g., .dmp). For example, if you export a table CUSTOMERS with 1 million rows, Data Pump imports all that data into ADB using DBMS_CLOUD.COPY_DATA after uploading the dump to OCI Object Storage. This ensures the content of your database is transferred intact.
Schemas (C): Data Pump imports schema definitions, including tables, views, indexes, triggers, and other objects owned by the schema. For instance, exporting a schema HR with tables like EMPLOYEES and DEPARTMENTS will recreate those objects in ADB, preserving their structure. The impdp utility or DBMS_CLOUD handles schema metadata, though some objects (e.g., indexes) may be recreated automatically by ADB's optimization.
The incorrect options are:
Tablespaces (A): Tablespaces are not imported directly. In Autonomous Database, storage is fully managed, and tablespaces are abstracted away. Data Pump imports data and schemas into ADB's managed tablespaces (e.g., DATA), not user-defined ones from the source. For example, a source tablespace USERS isn't replicated; its data is mapped to ADB's default storage.
Report (D): "Report" is not a database object; it might refer to query outputs or logs, but Data Pump doesn't import such entities. It focuses on database content, not external artifacts.
This process ensures a smooth migration of data and structure to ADB's managed environment.

NEW QUESTION # 89
A new Python developer has joined your team and needs to access the Autonomous Database dat a. How does the developer connect to and interact with the Autonomous Database from Python?

A. By using JDBC Driver
B. By using Oracle Client and the cx_Oracle interface
C. By using Oracle Client and the DBD-oracle interface
D. By using SQL Developer

Answer: B

Explanation:
Python developers connect to Autonomous Database using a dedicated library:
Correct Answer (D): "By using Oracle Client and the cx_Oracle interface" (now renamed oracledb) is the recommended method. The Oracle Client provides the underlying connectivity, and cx_Oracle (or oracledb) is a Python module for database access, supporting wallet-based authentication to Autonomous Database.
Incorrect Options:
A: SQL Developer is a GUI tool, not a Python interface.
B: DBD-oracle is not a standard Python library for Oracle; it's likely a typo or confusion with Perl's DBI.
C: JDBC is for Java, not Python; it's incompatible without a bridge like JPype.
This method ensures efficient, secure Python integration.

NEW QUESTION # 90
Which is a feature of a graph query language?

A. Scripting language
B. Run key-value queries
C. Object-oriented language
D. Ability to specify patterns

Answer: D

Explanation:
Graph query languages, like Oracle's Property Graph Query Language (PGQL), are designed for graph databases:
Correct Answer (D): "Ability to specify patterns" is a defining feature. Graph queries excel at defining and matching patterns (e.g., nodes and edges) to explore relationships, such as finding paths or subgraphs, critical for applications like social network analysis or fraud detection.
Incorrect Options:
A: Key-value queries are typical of NoSQL key-value stores, not graph databases.
B: While scripting may be possible in some contexts, it's not a core feature of graph query languages.
C: Graph query languages are not inherently object-oriented; they focus on relational graph structures.
This pattern-matching capability distinguishes graph queries from other query paradigms.

NEW QUESTION # 91
Which statement is NOT correct when the Autonomous Database is stopped?

A. Tools are no longer able to connect to a stopped instance.
B. CPU billing is halted.
C. User with DWROLE can still access the database.
D. In-flight transactions and queries are stopped.

Answer: C

Explanation:
When an Autonomous Database is stopped, its operational state changes significantly:
Correct Answer (C): "User with DWROLE can still access the database" is not correct. When the database is stopped, all access is disabled, including for users with roles like DWROLE (a predefined role for Data Warehouse tasks). The database is offline, and no connections or operations are possible until it is restarted.
True Statements:
A: Tools (e.g., SQL Developer, JDBC clients) cannot connect to a stopped instance because the database services are unavailable.
B: In-flight transactions and queries are terminated upon stopping, with any uncommitted changes rolled back to maintain data consistency.
D: CPU billing ceases when the database is stopped, though storage billing continues, reflecting Oracle's pay-per-use model for compute resources.
This behavior ensures resource conservation and cost control while maintaining data integrity.

NEW QUESTION # 92
......

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