也許你在其他相關網站上也看到了與 Oracle 1z0-1195-26 認證考試相關的相關培訓工具，但是我們的 PDFExamDumps在IT 認證考試領域有著舉足輕重的地位。PDFExamDumps研究的材料可以保證你100%通過考試。有了PDFExamDumps你的職業生涯將有所改變，你可以順利地在IT行業中推廣自己。當你選擇了PDFExamDumps你就會真正知道你已經為通過Oracle 1z0-1195-26認證考試做好了準備。我們不僅能幫你順利地通過考試還會為你提供一年的免費服務。
| Section | Objectives |
|---|---|
| Topic 1: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Create an Autonomous AI Database Serverless instance for a basic workload - Describe Autonomous AI Database characteristics, offerings, and deployment choices |
| Topic 2: Implementing Select AI and AI Vector Search in Autonomous AI Database | - Determine how AI Vector Search supports GenAI pipelines and RAG - Describe Select AI in Autonomous AI Database - Apply AI Vector Search to combined semantic and business-data search scenarios |
| Topic 3: Working with JSON and Graph in Oracle AI Database | - Explain JSON and Oracle AI Database JSON capabilities - Describe core graph concepts and graph analytic capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
| Topic 4: Working with AI and Vector Foundations | - Apply vector distance and indexing concepts to similarity search needs - Explain vectors, embeddings, and the Oracle VECTOR data type - Describe AI, AGI, and machine learning foundations |
| Topic 5: Using Oracle Database Actions and Data Studio Tools | - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks - Describe Database Actions and core development tools |
| Topic 6: Building Low-Code Applications and Agentic AI | - Choose the appropriate Agent Factory capability for a no-code AI agent use case - Describe Oracle APEX as Oracle's low-code platform |
PDFExamDumps的經驗豐富的專家團隊開發出了針對Oracle 1z0-1195-26 認證考試的有效的培訓計畫，很適合參加Oracle 1z0-1195-26 認證考試的考生。PDFExamDumps為你提供的都是高品質的產品，可以讓你參加Oracle 1z0-1195-26 認證考試之前做模擬考試，可以為你參加考試做最好的準備。
問題 #19
How does Oracle APEX help developers build applications with Oracle Database data?
答案：D
解題說明：
Oracle APEX is Oracle's low-code application development platform and is tightly integrated with Oracle Database. Oracle documentation describes APEX as providing browser-based enterprise application development with direct access to Oracle Database data. Developers configure pages, components, workflows, data sources, reports, forms, and business logic declaratively through App Builder rather than constructing every layer manually.
APEX explicitly embraces SQL. Developers can use SQL and PL/SQL to query and manipulate database- resident information while leveraging declarative components to minimize conventional coding effort.
Because the application engine operates close to the database, applications also inherit Oracle capabilities for transactions, security, concurrency, availability, analytics, and data management. Autonomous AI Database includes Oracle APEX capabilities and allows developers to create APEX workspaces and applications directly against database data.
APEX is therefore neither a disconnected application platform nor a command-line scripting framework. It is also distinct from Graph Studio and graph analytics capabilities used for operations such as community detection. The defining characteristics relevant to this question are its browser-based low-code development environment and native access to Oracle Database through SQL. The uploaded question bank confirms option B.
Study Guide reference: Building Low-Code Applications and Agentic AI - Oracle APEX, App Builder, browser-based development, and SQL integration.
問題 #20
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 #21
A support portal must search product manuals semantically while also filtering results by product line and support level stored in relational columns. How does Oracle AI Vector Search support this requirement?
答案：B
解題說明：
Oracle AI Vector Search supports semantic similarity search together with conventional relational predicates in SQL , making option C correct. The uploaded source explicitly identifies this integrated approach. Oracle AI Database 26ai provides the native VECTOR data type so embeddings can reside directly alongside relational business attributes. Oracle states that AI-powered vector similarity searches can be combined with business-data searches using SQL and the full capabilities of the converged database.
For the support portal, each manual or document chunk can have an embedding while relational columns identify its product line, entitlement level, version, or support tier. A SQL statement can restrict rows using predicates such as product line and support level while ordering eligible records by vector distance from the user's query embedding.
This approach is superior to retrieving a broad semantic result set and filtering it later in application code.
External post-filtering can waste processing and may remove highly ranked records without correctly replacing them with the next eligible matches.
Document APIs and property graphs are also not prerequisites. Oracle's converged architecture permits relational and vector criteria to operate together directly.
Study Guide reference: Implementing Select AI and AI Vector Search in Autonomous AI Database - hybrid business filtering, vector similarity ranking, and integrated SQL.
問題 #22
A bank wants to identify indirect money movement patterns across several accounts to support fraud investigation. Which approach fits this requirement?
答案：B
解題說明：
Modeling accounts as vertices and transfers as edges is the appropriate graph design because the investigation depends on discovering relationships and multi-hop transaction paths. The uploaded source explicitly designates this model as correct. Oracle Property Graph documentation confirms that graphs represent linked information using vertices, edges, and associated properties and are suitable for pattern matching, path finding, community detection, and other relationship-centric analytics.
In this banking scenario, each account can become a vertex containing account attributes, while each transfer becomes a directed edge containing properties such as amount, timestamp, or transaction type. Graph traversal can then follow transfers across multiple intermediary accounts and reveal patterns that are difficult to identify from isolated transaction rows.
This is particularly valuable for fraud investigation because suspicious activity may involve chains, rings, circular movements, intermediaries, or highly connected accounts rather than one anomalous transaction.
Keyword searching transaction descriptions does not analyze relationships. Summary balances discard essential connectivity information, while one-transaction-at-a-time reporting prevents efficient multi-hop analysis.
The technical requirement is therefore fundamentally graph-oriented: determine how entities are connected and analyze paths among those entities.
Study Guide reference: Working with JSON and Graph in Oracle AI Database - property graphs, vertices, edges, path analysis, and fraud-oriented relationship analysis.
問題 #23
A team already uses Database Actions and now needs the part of the environment focused on discovery, load, integration, and cataloging. Which workspace should they open?
答案：A
解題說明：
Data Studio is the Database Actions workspace specifically designed for data-oriented activities such as loading, discovering, cataloging, transforming, integrating, analyzing, and preparing data. The uploaded source marks Data Studio as the correct option. Oracle's current Autonomous AI Database documentation states that Data Studio enables users to load, discover, catalog, transform, analyze, share, enrich, and automate data workflows through a web-based interface.
Data Studio contains purpose-built tools including Data Load , Catalog , Data Transforms , Data Analysis
, and Data Insights . Catalog provides a central mechanism for browsing, searching, discovering, inspecting, and acting on local or connected data assets, while Data Transforms supports graphical data integration and transformation workflows.
The alternatives perform different functions. Database Users handles user administration. Graph Studio focuses on graph modeling and analytics. SQL Worksheet provides interactive execution of SQL and PL/SQL rather than an integrated discovery, cataloging, and loading environment.
Therefore, when the question combines the terms discovery, load, integration, and cataloging , Data Studio is the definitive Oracle workspace.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Data Studio, Data Load, Catalog, and Data Transforms.
問題 #24
......
PDFExamDumps的1z0-1195-26考古題的命中率很高，可以幫助大家一次通過考試。這是經過很多考生證明過的事實。所以不用擔心這個考古題的品質，這絕對是最值得你信賴的考試資料。如果你還是不相信的話，那就趕快自己來體驗一下吧。你绝对会相信我的话的。
1z0-1195-26題庫更新資訊: https://www.pdfexamdumps.com/1z0-1195-26_valid-braindumps.html