Master the Oracle Analytics Cloud 2025 Professional exam with our comprehensive Q&A collection. Review questions by topic, understand explanations, and build confidence for exam day.
Strategies to help you tackle Oracle Analytics Cloud 2025 Professional exam questions effectively
Allocate roughly 1-2 minutes per question. Flag difficult questions and return to them later.
Pay attention to keywords like 'MOST', 'LEAST', 'NOT', and 'EXCEPT' in questions.
Use elimination to narrow down choices. Often 1-2 options can be quickly ruled out.
Focus on understanding why answers are correct, not just memorizing facts.
Practice with real exam-style questions for Oracle Analytics Cloud 2025 Professional
Oracle Analytics Catalog is correct because it serves as the centralized repository for storing all OAC artifacts including visualizations, datasets, data flows, analyses, and dashboards. The Oracle Analytics Repository refers to the RPD (metadata repository) used in semantic modeling. The Semantic Model Layer is for data modeling structures, not storage. Data Warehouse Service is an external database service, not an OAC component for storing analytics artifacts.
Using AGO() function with Year level is the most appropriate approach because AGO() is specifically designed for time-based calculations and allows you to reference values from previous time periods. The formula would be ((Sales - AGO(Sales, Year, 1)) / AGO(Sales, Year, 1)) * 100. While % Difference From can work, AGO() provides more flexibility and control. TIMESTAMPADD is for date arithmetic, not comparative calculations. RANK() is for ordering data, not calculating growth percentages.
The physical layer not being updated is the correct answer because in OAC's semantic model architecture, new database columns must first be imported or added to the physical layer of the RPD, then mapped through the logical layer to be available to users. After updating the RPD, it must be published to take effect. While privilege issues could prevent access, the question states the column is not appearing at all, suggesting it hasn't been added to the model. Connection pool restarts and browser cache are unlikely causes for missing columns in the semantic model.
OAuth 2.0 with client credentials is the recommended approach for server-to-server authentication in embedding scenarios because it provides secure, token-based authentication without requiring user credentials, supports automated token refresh, and follows industry best practices for API security. Basic authentication is less secure and not recommended for production. SAML SSO is for user authentication, not server-to-server API calls. API keys in cookies are insecure and inappropriate for server-side integration.
Analytics Node is correct because it handles the presentation services, including user interface requests, visualization rendering, and interactive analytics. This node type processes user interactions with dashboards and workbooks. Data Flow Nodes are dedicated to data preparation and transformation tasks. Database Node is not a standard OAC node type (databases are typically external). Administration Node is not a distinct node type in OAC architecture; administrative functions run on the analytics infrastructure.
Review Q&A organized by exam domains to focus your study
25% of exam • 3 questions
What is the primary purpose of Oracle Analytics Cloud Architecture and Administration in Data & Analytics?
Oracle Analytics Cloud Architecture and Administration serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Analytics Cloud 2025 Professional certification.
Which best practice should be followed when implementing Oracle Analytics Cloud Architecture and Administration?
When implementing Oracle Analytics Cloud Architecture and Administration, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Oracle Analytics Cloud Architecture and Administration integrate with other Oracle services?
Oracle Analytics Cloud Architecture and Administration integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
30% of exam • 3 questions
What is the primary purpose of Data Visualization and Analysis in Data & Analytics?
Data Visualization and Analysis serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Analytics Cloud 2025 Professional certification.
Which best practice should be followed when implementing Data Visualization and Analysis?
When implementing Data Visualization and Analysis, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Data Visualization and Analysis integrate with other Oracle services?
Data Visualization and Analysis integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
25% of exam • 3 questions
What is the primary purpose of Data Modeling and Semantic Layer in Data & Analytics?
Data Modeling and Semantic Layer serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Analytics Cloud 2025 Professional certification.
Which best practice should be followed when implementing Data Modeling and Semantic Layer?
When implementing Data Modeling and Semantic Layer, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Data Modeling and Semantic Layer integrate with other Oracle services?
Data Modeling and Semantic Layer integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
20% of exam • 3 questions
What is the primary purpose of Advanced Features and Integration in Data & Analytics?
Advanced Features and Integration serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Analytics Cloud 2025 Professional certification.
Which best practice should be followed when implementing Advanced Features and Integration?
When implementing Advanced Features and Integration, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Advanced Features and Integration integrate with other Oracle services?
Advanced Features and Integration integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
After reviewing these questions and answers, challenge yourself with our interactive practice exams. Track your progress and identify areas for improvement.
Common questions about the exam format and questions
The Oracle Analytics Cloud 2025 Professional exam typically contains 50-65 questions. The exact number may vary, and not all questions may be scored as some are used for statistical purposes.
The exam includes multiple choice (single answer), multiple response (multiple correct answers), and scenario-based questions. Some questions may include diagrams or code snippets that you need to analyze.
Questions are weighted based on the exam domain weights. Topics with higher percentages have more questions. Focus your study time proportionally on domains with higher weights.
Yes, most certification exams allow you to flag questions for review and return to them before submitting. Use this feature strategically for difficult questions.
Practice questions are designed to match the style, difficulty, and topic coverage of the real exam. While exact questions won't appear, the concepts and question formats will be similar.
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