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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Using Oracle Database Actions and Data Studio Tools | 15% | - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks - Describe Database Actions and core development tools |
| Topic 2: Working with JSON and Graph in Oracle AI Database | 20% | - Distinguish when graph capabilities and Property Graph Views fit a business use case - Explain JSON and Oracle AI Database JSON capabilities - Describe core graph concepts and graph analytic capabilities |
| Topic 3: Working with AI and Vector Foundations | 15% | - Explain vectors, embeddings, and the Oracle VECTOR data type - Describe AI, AGI, and machine learning foundations - Apply vector distance and indexing concepts to similarity search needs |
| Topic 4: Building Low-Code Applications and Agentic AI | 10% | - Choose the appropriate Agent Factory capability for a no-code AI agent use case - Describe Oracle APEX as Oracle's low-code platform |
| Topic 5: Implementing Select AI and AI Vector Search in Autonomous AI Database | 20% | - Apply AI Vector Search to combined semantic and business-data search scenarios - Describe Select AI in Autonomous AI Database - Determine how AI Vector Search supports GenAI pipelines and RAG |
| Topic 6: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | 20% | - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Create an Autonomous AI Database Serverless instance for a basic workload |
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NEW QUESTION # 19
You just provisioned a Serverless database and need to confirm when application teams can begin connecting to it. When is the database ready for connections?
Answer: B
Explanation:
The database should be treated as ready after provisioning completes and its lifecycle state becomes Available
. The uploaded question source explicitly identifies this state as the correct readiness point. Oracle Autonomous AI Database documentation uses Available as the operational lifecycle state for an instance and requires that state for numerous database-management operations. Oracle's connection documentation then describes applications and client tools connecting to an existing Autonomous AI Database through supported Oracle Net Services and built-in tools.
Selecting Create only initiates the provisioning workflow. OCI still has to allocate and configure the underlying service resources before the database becomes operational. Loading a JSON collection is an application-data activity performed after database availability and is unrelated to whether the database service itself is ready. Likewise, Data Studio is a built-in data-management environment; creation or use of a Data Studio workflow is not a prerequisite for normal database connectivity.
For certification purposes, the decisive distinction is between provisioning initiated and provisioning completed . The Available lifecycle status indicates that the service has completed the provisioning process sufficiently for normal database use.
Study Guide reference: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics - Serverless provisioning, lifecycle states, and database connectivity.
NEW QUESTION # 20
How can developers access JSON Duality Views?
Answer: C
Explanation:
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.
NEW QUESTION # 21
Modern applications often need to work with relational data, JSON documents, graph relationships, and vector embeddings. What challenge does using a different specialized database for each need create?
Answer: C
Explanation:
Using a different point-solution database for each data model can create data silos , increasing integration, synchronization, governance, and operational complexity. The uploaded assessment identifies option D as correct. Oracle AI Database 26ai is explicitly positioned as a converged database platform supporting AI, graph, document, spatial, relational, and other application models within one database architecture.
The problem with separate specialized stores is that an application may need to duplicate relational records into a document database, copy embeddings into a vector database, and maintain relationships in a graph database. These copies must remain synchronized as source data changes. Security controls, backups, monitoring, patching, access policies, and application integrations may also differ across platforms.
Oracle's converged model instead allows different representations and workloads to operate on centrally governed data. Oracle specifically notes that the converged platform provides synergy among multiple data models and enables different types of information to be joined and manipulated together.
Therefore, separate databases do not automatically share security or eliminate transformation. Those are precisely the architectural burdens that convergence is intended to reduce.
Study Guide reference: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics - converged database strategy and elimination of data silos.
NEW QUESTION # 22
Which output can Select AI deliver to an application?
Answer: D
Explanation:
Comprehensive and Detailed 100 to 150 words of Explanation From Oracle AI Database topics:
Select AI supports multiple response modes depending on the action requested. With the default runsql action, Oracle generates SQL from the natural-language prompt, executes it, and returns the resulting data. The showsql action returns the generated SQL statement without executing it, while narrate executes the generated query and sends its results to the configured LLM to produce a natural-language description. Oracle additionally supports actions such as explainsql, chat, and summarize. Therefore, an application can receive a database result set, generated SQL, or a narrative response depending on how Select AI is invoked. Graph visualizations, patch-history maintenance recommendations, and automatic JSON export files are not Select AI output modes. This directly aligns with Oracle's Select AI actions and natural-language database interaction capabilities.
NEW QUESTION # 23
A manufacturer needs graph analysis that reflects inserts and updates from operational tables immediately.
How does a Property Graph View support this requirement?
Answer: C
Explanation:
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.
NEW QUESTION # 24
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