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| Section | Weight | Objectives |
|---|---|---|
| Data Management and Oracle Data Platform Overview | ~11% | - Data management concepts and data types - Modern data platform value and architecture - Oracle Data Strategy and multi-cloud deployment models |
| Oracle Database Services — Exadata, DBCS, and Engineered Systems | ~11% | - Exadata architecture and features - Database Cloud Service (DBCS) characteristics |
| MySQL HeatWave and NoSQL Services | ~11% | - MySQL HeatWave architecture and analytics - Oracle NoSQL Database features and use cases |
| Security, Resilience, and Cloud Integration | ~21% | - Cloud-native database services and deployment strategies - High availability, backup, and disaster recovery - Database security architectures and data protection |
| Converged Database — Multi-Model and AI Capabilities | ~15% | - JSON, Graph, Spatial, and key-value data support - Select AI and natural language querying - Oracle AI Vector Search concepts |
| Autonomous AI Database and Tools | ~16% | - Shared vs dedicated infrastructure - Core features of Autonomous AI Database - Built-in management and query tools |
| Oracle Machine Learning and AI Integration | ~15% | - AI agents and LLM integration - In-database machine learning algorithms - Oracle Data Studio and visualization |
每個人心裏都有一個烏托邦的夢，夢境的虛有讓人覺得心灰意冷，在現實中，其實這並不是虛有的，只要你採取一定的方是方法，一切皆有可能。Oracle的1z0-1195-26考試認證將會從遙不可及變得綽手可得。這是為什麼呢，因為有VCESoft Oracle的1z0-1195-26考試培訓資料在手，VCESoft Oracle的1z0-1195-26考試培訓資料是IT認證最好的培訓資料，它以最全最新，通過率最高而聞名，而且省時又省力，有了它，你將輕鬆的通過考試。實現了你的夢想，你就有了自信，有了自信你將走向成功。
問題 #32
Which example is a common AI use case?
答案：C
解題說明：
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Fraud detection is a standard AI use case because machine-learning and anomaly-detection models can identify unusual behavioral patterns across transaction attributes such as amount, account, merchant, location, and historical activity. Oracle documents AI-driven fraud-prevention architectures that analyze transaction behavior and flag suspicious or anomalous activity for investigation. The other options are administrative database or network tasks rather than AI inference problems. Alphabetically listing tables is ordinary metadata browsing; rotating an encryption key is deterministic security administration; and assigning a subnet CIDR is infrastructure configuration. None requires a model to learn patterns from data. Detecting fraudulent transactions from behavior patterns therefore best represents an AI workload and aligns with the Oracle AI Database foundations coverage of practical AI domains and use cases. Oracle Docs
問題 #33
Which set of tools is specifically highlighted as available from Database Actions?
答案：C
解題說明：
The Database Actions environment specifically includes SQL, Data Modeler, REST, JSON, Oracle Machine Learning, and Oracle APEX , making option C correct. The uploaded assessment identifies the same tool set. Oracle's current Autonomous AI Database documentation describes Database Actions as a web- based interface for development, data tooling, administration, and monitoring. Its Development area includes SQL, Data Modeler, REST, JSON, Charts, Scheduling, Oracle Machine Learning, Spatial Studio, Graph Studio, and Oracle APEX.
SQL provides the browser-based worksheet for SQL and PL/SQL execution. Data Modeler supports database modeling and diagramming. REST provides tools for database REST services and APIs. JSON provides facilities for working with JSON collections and documents. Oracle Machine Learning exposes integrated ML development capabilities, while APEX launches Oracle's low-code application-development environment.
Oracle's Machine Learning documentation likewise identifies Database Actions as the entry point for Oracle Machine Learning.
The remaining choices largely describe OCI infrastructure or security-management services rather than Database Actions development tools. Compute, block storage, load balancing, IAM, billing, private endpoints, and Vault are managed elsewhere in OCI.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Database Actions Launchpad and Development tools.
問題 #34
What does Select AI enable in Autonomous AI Database?
答案：B
解題說明：
Select AI enables users to interact with Autonomous AI Database by expressing requests in natural language rather than manually constructing SQL. Oracle documents that Select AI uses generative AI and large language models to convert natural-language input into Oracle SQL. Depending on the requested action, the generated SQL can be displayed, explained, executed, or its results can be transformed into a natural-language response. This makes database information accessible to users who understand the business question but may not know SQL syntax or the underlying schema.
Internally, Select AI can augment a prompt with schema metadata, interact with the configured LLM, generate SQL, run the query, and optionally narrate the resulting data. It also extends beyond NL2SQL into Retrieval-Augmented Generation, conversations, and other generative-AI capabilities. It does not replace relational SQL with graph pattern matching, manage encryption-key rotation, or provision Autonomous AI Database infrastructure. Those are unrelated database administration or graph functions. The supplied question bank explicitly marks the natural-language data-query capability as correct.
Study Guide reference: Implementing Select AI and AI Vector Search in Autonomous AI Database - Select AI, natural-language interaction, NL2SQL, and LLM integration.
問題 #35
Which task is a common use of graph analytics?
答案：A
解題說明：
Determining communities or connected clusters in a network is a canonical graph-analytics use case. The uploaded source identifies option D as the correct response. Oracle Property Graph documentation explicitly lists finding communities , influencers, recommendations, graph traversal, pattern matching, and path finding among typical graph-analysis operations. Oracle AI Database 26ai documentation also identifies Community Detection as a supported graph-analysis algorithm.
Community detection examines topology to identify groups of vertices that are more strongly connected with one another than with the remainder of the network. Examples include identifying customer communities in social networks, coordinated groups in fraud investigations, clusters of interconnected devices in telecommunications, or related entities in knowledge graphs.
The other choices deliberately discard the characteristic that makes graph analytics useful: relationships.
Listing unrelated records and sorting a scalar column are standard tabular operations. Storing relationships as isolated text values prevents the database from traversing and analyzing those relationships as graph edges.
Graph analytics becomes valuable when the question concerns connectivity, paths, neighborhoods, influence, centrality, clusters, or structural patterns rather than merely individual records and attributes.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - graph analytics, community detection, connectivity, and network analysis.
問題 #36
A team must deploy an Oracle Autonomous AI Database Serverless instance so that database access is available only inside a private OCI network.
Which access setting should they use?
答案：D
解題說明：
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Private endpoint access only is the correct network setting when an Autonomous AI Database Serverless instance must be reachable only through a private OCI network. Oracle documents that this option assigns a private endpoint, private IP address, and hostname and allows traffic only from the specified VCN, including supported peered or connected private networks. Public access is blocked unless explicitly enabled through separate advanced configuration. "Secure access from allowed IPs and VCNs only" is an ACL-based public- endpoint model and can permit approved public addresses, so it does not satisfy the stricter private-only requirement. "Secure access from everywhere" is broader still. Therefore, option D precisely matches the requirement to keep database access inside the private OCI network.
問題 #37
......
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