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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Converged Database — Multi-Model and AI Capabilities | ~15% | - JSON, Graph, Spatial, and key-value data support - Oracle AI Vector Search concepts - Select AI and natural language querying |
| Topic 2: Oracle Machine Learning and AI Integration | ~15% | - AI agents and LLM integration - Oracle Data Studio and visualization - In-database machine learning algorithms |
| Topic 3: Security, Resilience, and Cloud Integration | ~21% | - Database security architectures and data protection - Cloud-native database services and deployment strategies - High availability, backup, and disaster recovery |
| Topic 4: Oracle Database Services — Exadata, DBCS, and Engineered Systems | ~11% | - Database Cloud Service (DBCS) characteristics - Exadata architecture and features |
| Topic 5: Autonomous AI Database and Tools | ~16% | - Shared vs dedicated infrastructure - Core features of Autonomous AI Database - Built-in management and query tools |
| Topic 6: Data Management and Oracle Data Platform Overview | ~11% | - Oracle Data Strategy and multi-cloud deployment models - Data management concepts and data types - Modern data platform value and architecture |
| Topic 7: MySQL HeatWave and NoSQL Services | ~11% | - MySQL HeatWave architecture and analytics - Oracle NoSQL Database features and use cases |
據調查，現在IT行業認證考試中大家最想參加的是Oracle的1z0-1195-26考試。確實，這是一個非常重要的考試，這個考試已經被公開認證了。此外，這個考試資格可以證明你擁有了高技能。然而，和考試的重要性一樣，這個考試也是非常難的。要想通過考試是很困難的，但是請不要擔心。因為Fast2test可以幫助你通過困難的1z0-1195-26認證考試。
問題 #47
A project team wants a built-in workspace to analyze data assets and support sharing or collaboration after preparation work is complete.
Which choice fits that requirement?
答案：B
解題說明：
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Data Studio is the correct choice because Oracle positions it as the integrated, web-based data workspace inside Database Actions for loading, discovering, cataloging, transforming, analyzing, sharing, enriching, and automating data workflows. Its Data Analysis capability supports reports and visual analysis, while Data Share and Data Marketplace support governed distribution and collaboration after data preparation. SQL Worksheet is primarily for SQL and PL/SQL execution; Database Users is for user administration; and Private Endpoint configuration is a networking control, not a data-analysis workspace. Therefore, a team that needs to continue from prepared data into analysis and sharing should use Data Studio. This maps directly to the Oracle AI Database topic "Using Oracle Database Actions and Data Studio Tools." Oracle Docs
問題 #48
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 #49
Why do developers often use JSON in applications?
答案：D
解題說明：
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
JSON is widely used in application development because a JSON document can directly represent an application object, including hierarchical relationships through nested objects and arrays. Oracle's JSON- Relational Duality documentation specifically notes that a single JSON document can represent an application object directly and is self-contained and schema-flexible. Oracle AI Database also supports native JSON storage, indexing, querying, and transactional processing. Option A is incorrect because JSON does not require a fixed document schema before storage. Option B is incorrect because JSON is a data representation, not a replacement for APIs or CRUD operations. Option C is also false because JSON supports strings, numbers, booleans, null, objects, and arrays. Therefore, mapping naturally to application objects and nested structures is the strongest reason among the choices. Oracle Docs
問題 #50
How can developers access JSON Duality Views?
答案：A
解題說明：
Developers can access JSON-Relational Duality Views using document-oriented interfaces, including Oracle AI Database API for MongoDB , as well as SQL-based database interfaces. The uploaded source explicitly identifies "MongoDB-compatible APIs or SQL" as correct. Oracle documentation confirms that duality views expose relational table data as JSON documents and that applications can interact with the same underlying data either document-centrically or relationally.
With the MongoDB-compatible API, the duality view can be treated as a document collection by applications using familiar MongoDB drivers and development patterns. At the same time, because the authoritative data remains in Oracle relational tables, SQL and other relational capabilities can operate directly on the same information. This is a primary architectural advantage of JSON-Relational Duality.
No export into a separate document store is necessary; doing so would reintroduce data duplication and synchronization problems that duality views are designed to avoid. Graph visualization is unrelated to document access, and although APEX applications can consume database data, APEX-specific PL/SQL packages are not the principal interface defining duality-view access.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - JSON Duality Views, Oracle AI Database API for MongoDB, SQL access, and unified relational/document development.
問題 #51
A manufacturer needs graph analysis that reflects inserts and updates from operational tables immediately.
How does a Property Graph View support this requirement?
答案：A
解題說明：
A Property Graph View provides a graph interpretation directly over data stored in relational database tables rather than requiring a separately maintained copy of that data. Oracle documents the Property Graph View as a view-like object containing metadata describing vertices, edges, labels, keys, and properties. Because the underlying graph information remains in the referenced relational tables, modifications to those tables are immediately reflected when the graph is queried.
This architecture directly satisfies the manufacturer's requirement. When operational applications insert or update rows in the underlying objects, graph queries subsequently operate against the updated relational data through the graph metadata definition. There is no required intermediate conversion to JSON and no scheduled batch refresh of a separate graph copy. Oracle also supports direct graph queries against database- resident property graph structures, including pattern matching through database graph-query facilities.
A separate in-memory graph server can be used for certain advanced analytics scenarios, but that does not change what a database Property Graph View fundamentally provides. The key exam distinction is metadata- based graph representation over existing database objects versus duplicated graph storage requiring synchronization. Therefore, option D precisely matches the required real-time operational behavior.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - Property Graph Views, metadata-based graph modeling, and relational-table integration.
問題 #52
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