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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security, Integration and Data Management | 20% | - Load, migrate and integrate data from various sources - Configure identity and access management - Use Autonomous Database tools for development and administration - Implement data encryption and security controls |
| Topic 2: AI Features and Capabilities | 30% | - Apply AI-assisted performance tuning and optimization - Configure and use AI Vector Search - Use Oracle Machine Learning within Autonomous Database - Implement Select AI for natural language to SQL generation |
| Topic 3: Database Management and Operations | 25% | - Perform patching, upgrades and lifecycle management - Monitor and manage database performance and resources - Implement backup, recovery and high availability strategies - Configure auto-scaling and storage management |
| Topic 4: Autonomous Database Architecture and Provisioning | 25% | - Describe Autonomous Database architecture and core components - Provision and configure Autonomous Database on shared infrastructure - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Provision and configure Autonomous Database on dedicated infrastructure |
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NEW QUESTION # 58
Which statement is true about connecting a marketplace Oracle Cloud Infrastructure (OCI) image to an Autonomous Database on Shared Infrastructure?
Answer: D
NEW QUESTION # 59
Which two license types does the customer need to benefit from BYOL when leveraging on-premise Enterprise Database licenses in Oracle Autonomous Database?
Answer: A,B
Explanation:
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.
NEW QUESTION # 60
You have been tasked with analyzing a year’s worth of sales data stored in an Autonomous Data Warehouse instance. Which tool would you use to automate data exploration and create pivot tables?
Answer: A
Explanation:
Full Detailed In-Depth Explanation:
A: False. APEX is for app development, not data exploration.
B: False. SQL Developer Web is for SQL queries, not pivot tables.
C: True. Business Models in ADW automates data exploration and generates pivot tables.
D: False. Data Load is for importing data, not analysis.
NEW QUESTION # 61
You have a requirement to create an Autonomous Transaction Processing database that can support at least 200 concurrent statements per OCPU as well as parallelism. Which service will you need to connect to?
Answer: B
Explanation:
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.
NEW QUESTION # 62
A corporation is building a web application to allow its customers to schedule service requests online. There is also a need to run operational reports at times during non-peak hours. The architecture team is debating whether such reports should be run on the OLTP database or in a separate data mart. The DBA Manager does not want to add any more admin responsibility to the team and is looking for a database option that’s low to zero maintenance, but meets their strict performance requirements as well. Which Oracle Cloud Infrastructure database service is appropriate for this scenario?
Answer: C
Explanation:
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.
NEW QUESTION # 63
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