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| Section | Weight | Objectives |
|---|---|---|
| Data Management and Oracle Data Platform Overview | ~11% | - Modern data platform value and architecture - Data management concepts and data types - Oracle Data Strategy and multi-cloud deployment models |
| Oracle Database Services — Exadata, DBCS, and Engineered Systems | ~11% | - Database Cloud Service (DBCS) characteristics - Exadata architecture and features |
| Autonomous AI Database and Tools | ~16% | - Shared vs dedicated infrastructure - Core features of Autonomous AI Database - Built-in management and query tools |
| Security, Resilience, and Cloud Integration | ~21% | - Cloud-native database services and deployment strategies - Database security architectures and data protection - High availability, backup, and disaster recovery |
| Oracle Machine Learning and AI Integration | ~15% | - In-database machine learning algorithms - AI agents and LLM integration - Oracle Data Studio and visualization |
| MySQL HeatWave and NoSQL Services | ~11% | - Oracle NoSQL Database features and use cases - MySQL HeatWave architecture and analytics |
| 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 |
>> Real 1z0-1195-26 Exam Questions <<
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NEW QUESTION # 24
A data analyst wants to discover data, load it into the platform, and prepare it for later use without leaving the built-in tools. Which workspace fits this task?
Answer: D
Explanation:
Data Studio is the correct built-in workspace because its purpose directly covers data discovery, loading, preparation, transformation, analysis, cataloging, sharing, and related self-service workflows. The uploaded source designates Data Studio as the correct answer. Oracle's current Autonomous AI Database documentation states that Data Studio can be used to load, discover, catalog, transform, analyze, share, enrich, and automate data workflows through a web-based interface.
Data Studio is available through Database Actions and contains specialized tools including Data Load , Catalog , Data Transforms , Data Analysis , and Data Insights . Data Load can ingest or link data from local files, remote databases, cloud storage, and live feeds, while Catalog supports searching, discovering, inspecting, and managing available data assets.
OCI Vault addresses secrets and encryption-key management rather than data preparation.
VECTOR_DISTANCE is an individual SQL function used for vector comparisons, not an integrated analyst workspace. A Property Graph View defines a graph representation over data but likewise does not provide general discovery and loading functionality.
Study Guide reference: Using Oracle Database Actions and Data Studio Tools - Data Studio, Data Load, Catalog, Data Transforms, and self-service data preparation.
NEW QUESTION # 25
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: A
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 # 26
Which set of tools is specifically highlighted as available from Database Actions?
Answer: D
Explanation:
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.
NEW QUESTION # 27
Why do developers often use JSON in applications?
Answer: A
Explanation:
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
NEW QUESTION # 28
A business wants one data platform where semantic similarity, relational consistency, and SQL-based filtering all work together.
Which statement aligns with this design goal?
Answer: A
NEW QUESTION # 29
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