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| Section | Weight | Objectives |
|---|---|---|
| Database Management and Operations | 25% | - Implement backup, recovery and high availability strategies - Perform patching, upgrades and lifecycle management - Monitor and manage database performance and resources - Configure auto-scaling and storage management |
| Autonomous Database Architecture and Provisioning | 25% | - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Provision and configure Autonomous Database on shared infrastructure - Describe Autonomous Database architecture and core components - Provision and configure Autonomous Database on dedicated infrastructure |
| AI Features and Capabilities | 30% | - Configure and use AI Vector Search - Use Oracle Machine Learning within Autonomous Database - Apply AI-assisted performance tuning and optimization - Implement Select AI for natural language to SQL generation |
| Security, Integration and Data Management | 20% | - Use Autonomous Database tools for development and administration - Implement data encryption and security controls - Configure identity and access management - Load, migrate and integrate data from various sources |
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NEW QUESTION # 108
Oracle Data Safe is a unified control center for your Oracle databases which helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements. Which statement is FALSE for Oracle Data Safe?
Answer: A
Explanation:
Oracle Data Safe enhances database security across various Oracle environments. The false statement is:
Oracle Data Safe only supports Autonomous Database (D): This is incorrect. Oracle Data Safe supports a wide range of Oracle databases, not just Autonomous Database. It works with Autonomous Database (shared and dedicated), Oracle Database Cloud Service (VM and Bare Metal), Exadata DB Systems, on-premises Oracle Databases, and Oracle Database on OCI Compute. For example, a DBA could use Data Safe to mask sensitive data in an on-premises 19c database or assess security in an Exadata Cloud@Customer deployment, not just ADB. This broad compatibility makes it a unified security tool across Oracle’s ecosystem.
The true statements are:
Oracle Data Safe helps you find sensitive data in your database by inspecting the actual data in your database and its data dictionary (A): Data Safe’s Data Discovery feature scans tables and metadata to identify sensitive columns (e.g., SSNs, credit card numbers), using predefined and custom patterns.
Oracle Data Safe helps you assess the security of your cloud database configurations by analyzing database configurations (B): The Security Assessment feature evaluates settings like encryption, auditing, and privileges, providing risk scores and recommendations.
Oracle Data Safe evaluates user types, how users are authenticated, and the password policies assigned to each user (C): User Assessment analyzes user accounts, authentication methods (e.g., password, SSO), and policies, highlighting risks like weak passwords.
The misconception in D limits Data Safe’s scope, which extends beyond ADB to all supported Oracle databases.
NEW QUESTION # 109
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?
Answer: C
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 # 110
Which Oracle package is used to load data to an Autonomous Database from object storage?
Answer: B
Explanation:
Loading data into Autonomous Database from object storage (e.g., OCI Object Storage) relies on a specific PL/SQL package. The correct answer is:
DBMS_CLOUD (D): The DBMS_CLOUD package is Oracle’s cloud-native tool for interacting with external data sources, including object storage, in Autonomous Database. It provides procedures like DBMS_CLOUD.COPY_DATA to load data from files (e.g., CSV, JSON, Parquet) stored in OCI Object Storage buckets into ADB tables. For example, to load a CSV file sales.csv from a bucket, you’d:
BEGIN
DBMS_CLOUD.CREATE_CREDENTIAL(credential_name => 'OBJ_STORE_CRED', username => 'oci_user', password => 'auth_token'); DBMS_CLOUD.COPY_DATA(table_name => 'SALES', credential_name => 'OBJ_STORE_CRED', file_uri_list => 'https://objectstorage.region.oraclecloud.com/n/namespace/b/bucket/o/sales.csv', format => json_object('type' value 'csv')); END; This package handles authentication (via OCI credentials), file parsing, and data insertion, supporting formats like text, Avro, and ORC. It’s integral to ADB’s cloud integration, abstracting low-level operations and ensuring security (e.g., via IAM auth).
The incorrect options are:
DBMS_RPC (A): This package doesn’t exist in Oracle Database. It might be a typo or confusion with remote procedure calls, unrelated to data loading.
DBMS_LOAD (B): No such package exists. It might confuse with SQL*Loader, but that’s a separate utility, not a PL/SQL package, and isn’t used directly in ADB for object storage.
DBMS_MIGRATE (C): This doesn’t exist either. It might be a misnomer for DBMS_DATAPUMP (for Data Pump), but that’s for database migration, not object storage loading.
DBMS_CLOUD is purpose-built for ADB’s cloud-first architecture, making data ingestion seamless and efficient.
NEW QUESTION # 111
Which management operation is correct about Autonomous Databases on Shared Exadata Infrastructure?
Answer: C
Explanation:
Management operations for Autonomous Databases on Shared Exadata Infrastructure are limited due to its fully managed nature. The correct statement is:
You cannot configure the scheduling for your Autonomous Databases on Shared Exadata Infrastructure (C): In shared infrastructure, Oracle fully controls maintenance scheduling (e.g., patching, upgrades). Unlike dedicated infrastructure, where users can set maintenance windows, shared ADB users cannot adjust timing. Oracle notifies users of upcoming maintenance (e.g., via email or console), typically in a 7-day window, but the exact schedule is Oracle-driven to optimize the shared Exadata platform. For example, a quarterly patch might occur on a Tuesday at 2 AM UTC, and users must adapt, not reschedule.
The incorrect options are:
You can skip a scheduled maintenance run... (A): False. Shared infrastructure does not allow skipping maintenance runs, even for two quarters. This flexibility exists only in dedicated infrastructure, where users have more control (e.g., skipping up to two consecutive updates). In shared mode, Oracle enforces updates for security and stability across all tenants.
You can perform a "rolling restart"... (B): False. Rolling restarts (restarting nodes sequentially for availability) are not user-initiated in ADB shared infrastructure. Restarts, if needed, are managed by Oracle during maintenance, and users cannot control the process or ensure node-by-node availability.
You can choose to use Release Update or Release Update Revision updates... (D): False. In shared infrastructure, Oracle applies Release Updates (RUs) uniformly across all databases; users cannot choose between RU or Release Update Revisions (RURs), a feature reserved for dedicated deployments.
This reflects the trade-off of shared infrastructure: lower cost and management effort for less control.
NEW QUESTION # 112
Which predefined role that exists in Autonomous Database includes common privileges that are used by a Data Warehouse developer? (Choose the best answer.)
Answer: B
Explanation:
Autonomous Database provides predefined roles tailored to specific use cases. The correct answer is:
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.
NEW QUESTION # 113
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