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Oracle 1Z0-931-25 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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 4	Developing on Autonomous Database: This section of the exam measures the skills of Application Developers and focuses on developing and extending applications using Autonomous Database. It covers using generative AI for natural language queries, Autonomous JSON Database, Oracle Text for document search, location-based analysis with Autonomous Spatial, Autonomous Graph for data relationships, and integration with Object Storage, enabling developers to build intelligent, scalable applications.
Topic 5	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 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.

Oracle Autonomous Database Cloud 2025 Professional Sample Questions (Q111-Q116):

NEW QUESTION # 111
Which two statements apply to the Autonomous Database service on Dedicated Infrastructure? (Choose two.)

A. You can set maintenance windows for each individual Autonomous Container Database
B. Patching occurs on the first Sunday of each quarter
C. You, as the customer, are responsible for all patching operations
D. You can set maintenance windows for an Autonomous Exadata Infrastructure

Answer: A,C

Explanation:
Autonomous Database on Dedicated Infrastructure offers more control than shared infrastructure. The two correct statements are:
You, as the customer, are responsible for all patching operations (A): In dedicated infrastructure, customers manage patching for Autonomous Container Databases (ACDs) and Autonomous Databases (ADBs), unlike shared infrastructure where Oracle handles it. You choose when to apply Release Updates (RUs) or skip them (up to two quarters), using the OCI console or API (e.g., oci db autonomous-container-database update). For example, you might schedule an RU for an ACD on a Saturday night, downloading the patch from Oracle and applying it manually to minimize downtime. This responsibility comes with the dedicated model's flexibility.
You can set maintenance windows for each individual Autonomous Container Database (C): Dedicated infrastructure allows setting specific maintenance windows per ACD, not just at the Exadata Infrastructure level. In the OCI console, under each ACD's details, you configure a preferred time (e.g., "Sundays, 02:00-04:00 UTC"), ensuring patches or upgrades align with your schedule. For instance, ACD1 might patch Sundays, while ACD2 patches Tuesdays, tailoring downtime to different workloads.
The incorrect options are:
You can set maintenance windows for an Autonomous Exadata Infrastructure (B): Maintenance windows are set at the ACD level, not the broader Autonomous Exadata Infrastructure (AEI) level. AEI maintenance (e.g., hardware updates) is Oracle-managed, with notification but no customer scheduling.
Patching occurs on the first Sunday of each quarter (D): There's no fixed schedule like "first Sunday." In dedicated mode, you control patching timing within a quarter, notified by Oracle of available RUs, unlike shared infrastructure's Oracle-driven schedule.
These statements highlight dedicated infrastructure's customer-driven management.

NEW QUESTION # 112
Which option should you use to create a graph with Graph Studio?

A. Graph created by a special tool downloaded from oracle.com
B. A graph license key
C. Tables in an Autonomous Database instance
D. NoSQL configuration
E. Graph analytics algorithms

Answer: C

Explanation:
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.
E: A license key isn't a creation method; graph features are included with Autonomous Database.
This integrates graph capabilities with existing data.

NEW QUESTION # 113
Which native data type is used to store spatial information?

A. GEO_JSON
B. SDO_GEOMETRY
C. SDO_RELATE
D. SDO_LOCATION

Answer: B

Explanation:
Oracle Database supports spatial data with a dedicated data type:
Correct Answer (A): SDO_GEOMETRY is the native data type for storing spatial information, such as points, lines, and polygons, in a structured format compatible with spatial queries and operations.
Incorrect Options:
B: SDO_LOCATION is not a valid data type; it may be a confusion with SDO_GEOMETRY.
C: SDO_RELATE is a spatial operator for relationship analysis, not a storage type.
D: GEO_JSON is a format for spatial data, not a native Oracle data type (though it can be parsed into SDO_GEOMETRY).
This type enables advanced geospatial functionality.

NEW QUESTION # 114
In which four ways can Oracle Database optimally access data in Object Storage? (Choose four.)

A. Scan avoidance using columnar pruning for columnar stores like parquet and orc
B. Scan avoidance using columnar pruning for .csv files
C. Scan avoidance using block skipping when reading parquet and orc files
D. Optimized data archive using hybrid partitioned tables
E. Optimized data archive using partitioned external tables
F. Scan avoidance using partitioned external tables

Answer: A,D,E,F

Explanation:
Oracle Database provides several techniques to optimize data access from Object Storage, particularly in the context of Autonomous Database, leveraging external tables and advanced storage formats. The question asks for four correct methods, and based on Oracle documentation, the following are the most applicable:
Correct Answer (A): Scan avoidance using partitioned external tables
Partitioned external tables allow Oracle Database to skip irrelevant partitions when querying data stored in Object Storage. By organizing data into partitions (e.g., by date or region), the database engine can prune partitions that don't match the query predicates, significantly reducing the amount of data scanned and improving performance. This is a well-documented optimization for external data access in Oracle Database and Autonomous Database environments.
Correct Answer (D): Scan avoidance using columnar pruning for columnar stores like parquet and orc Columnar pruning is a technique where only the required columns are read from columnar file formats such as Parquet or ORC stored in Object Storage. These formats store data column-wise, enabling the database to avoid scanning entire rows or irrelevant columns, which is particularly efficient for analytical queries common in Autonomous Data Warehouse (ADW). This is a standard optimization supported by Oracle's external table framework when accessing Object Storage.
Correct Answer (E): Optimized data archive using hybrid partitioned tables Hybrid partitioned tables combine local database partitions with external partitions stored in Object Storage. This allows older, less frequently accessed data to be archived efficiently in the cloud while remaining queryable alongside active data in the database. The database optimizes access by seamlessly integrating these partitions, reducing costs and improving archival efficiency. This feature is explicitly supported in Oracle Database and enhanced in Autonomous Database for data lifecycle management.
Correct Answer (F): Optimized data archive using partitioned external tables Similar to hybrid partitioned tables, using partitioned external tables alone optimizes data archiving by storing historical data in Object Storage with partitioning (e.g., by year). This method enables efficient querying of archived data by pruning unneeded partitions, offering a cost-effective and scalable archival solution. It's a distinct approach from hybrid tables, focusing solely on external storage, and is widely used in Oracle environments.
Incorrect Options:
B . Scan avoidance using columnar pruning for .csv files
CSV files are row-based, not columnar, and lack the internal structure of formats like Parquet or ORC. While Oracle can read CSVs from Object Storage via external tables, columnar pruning is not applicable because CSVs don't support column-wise storage or metadata for pruning. This makes this option incorrect as a specific optimization technique, though basic predicate pushdown might still reduce scanning to some extent.
C . Scan avoidance using block skipping when reading parquet and orc files Block skipping (or row group skipping) is a feature in some database systems where metadata in Parquet or ORC files allows skipping entire blocks of data based on query filters. While Oracle supports Parquet and ORC through external tables and can leverage their columnar nature (via pruning), "block skipping" is not explicitly highlighted as a primary optimization in Oracle's documentation for Autonomous Database. It's more commonly associated with systems like Apache Spark or Hive. Oracle's focus is on columnar pruning and partitioning, making this option less accurate in this context.
Why Four Answers?
The question specifies "four ways," and while six options are provided, A, D, E, and F are the most directly supported and documented methods in Oracle Autonomous Database for optimizing Object Storage access. Options B and C, while conceptually related to data access optimizations, are either inapplicable (CSV lacks columnar structure) or not explicitly emphasized (block skipping) in Oracle's feature set for this purpose.
This selection aligns with Oracle's focus on partitioning and columnar formats for efficient cloud data access, ensuring both performance and archival optimization.
Reference:
External Tables and Object Storage
Hybrid Partitioned Tables
Autonomous Database Data Loading

NEW QUESTION # 115
Which three options are available to access data in an Autonomous JSON Database?

A. NoSQL statements using Simple Oracle Document Access (SODA) drivers
B. REST API calls to the database (not enabled by default)
C. Oracle Cloud Infrastructure console using the JSON Online Developer tool
D. Regular Oracle SQL statements using a connection through the listener
E. Oracle JSON Developer tool downloaded from Oracle Technology Network (OTN)

Answer: A,B,C

Explanation:
Full Detailed In-Depth Explanation:
Autonomous JSON Database supports:
A: True. SODA provides NoSQL-style access for JSON documents.
B: False. SQL is secondary; SODA/REST are primary for JSON data.
C: True. REST APIs are supported but require enablement.
D: True. The OCI console offers the JSON Online Developer tool.
E: False. No such downloadable tool exists for Autonomous JSON.

NEW QUESTION # 116
......

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