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| Section | Weight | Objectives |
|---|---|---|
| Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Managing analytics content - Creating and managing views - Creating and managing analyses |
| Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Securing Publisher content and access - Managing Oracle Analytics Publisher |
| Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Connecting to data sources - Migrating analytics artifacts |
| Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Creating and designing dashboards - Dashboard prompts and pages - Enhancing dashboards and briefing books |
| Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Managing filters - Formatting data - Using prompts and variables - Managing selection steps |
| Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating and managing data models - Creating reports |
| Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Report translations - Publisher administration - Scheduling reports - Bursting and delivery - Managing report data sources |
| Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Administration - Security and application roles - Performance and caching |
| Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Using RTF Template Builder - Using Layout Editor - Creating Excel and eText templates - Formatting and customizing reports |
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NEW QUESTION # 46
A reporting analyst creates a dashboard that includes multiple analyses sharing the same filter criteria. Users complain that updating each analysis separately is difficult. Which design approach improves maintainability?
Answer: C
Explanation:
A shared Dashboard Prompt with Presentation Variables centralizes user input and allows multiple dashboard analyses to reference the same runtime selection. Oracle defines a Presentation Variable as a variable populated through a dashboard column prompt or variable prompt. Each time the user changes the prompt selection, the presentation variable is assigned the selected value or values.
Analyses on the dashboard can then reference the variable in filters, expressions, titles, or other supported locations. This allows a department, fiscal period, region, or comparable filter criterion to be selected once and reused across multiple dashboard components.
The architecture substantially improves maintainability because the dashboard-level interaction is managed centrally rather than requiring a separate prompt or manually maintained filter mechanism for every analysis.
Independent prompts would recreate the exact maintenance problem stated in the scenario. Conditional Formatting changes visual presentation rather than providing shared filtering, while exporting analyses creates static outputs and eliminates the interactive dashboard experience.
Therefore, the correct design is A. Use a shared Dashboard Prompt with Presentation Variables .
Reference Topic: Designing, Creating, and Enhancing Dashboards - Dashboard Prompts and Presentation Variables
NEW QUESTION # 47
An administrator is configuring a delivery agent. The agent should deliver content to selected devices instead of using the user's active delivery profile, and the scheduled analysis run should seed the cache. Which two destination settings match these requirements?
Answer: E,F
Explanation:
For device delivery, Oracle Analytics distinguishes between Active Delivery Profile and Specific Devices .
Active Delivery Profile lets each user determine delivery behavior through personal delivery preferences.
When the Agent must instead target explicitly chosen device types, the author selects Specific Devices and identifies the permitted devices. This satisfies the requirement to avoid reliance on the user's active profile.
For cache seeding, Oracle documents a dedicated Agent workflow. After choosing the analysis or dashboard page and establishing recipients, the administrator clears ordinary user destinations and selects the Analytics Server/BI Server Cache destination. Scheduled execution then populates the query cache using the results generated by the Agent.
The terminology in the question uses Oracle BI Server Cache , while current Oracle Analytics Server documentation refers to Oracle Analytics Server Cache ; functionally, this is the same cache-seeding destination represented by option E.
Selecting Never wouldn't schedule cache seeding. Home Page and Dashboard creates analytics alerts rather than restricting delivery to email devices. Active Delivery Profile does the opposite of the requirement, and Printer isn't the standard cache-seeding destination.
Therefore, the correct selections are Specific Devices and Oracle BI Server Cache .
Reference Topic: Managing Administration, Security, and Performance - Agent Destinations and Cache Seeding
NEW QUESTION # 48
An administrator wants to ensure that only authenticated users with appropriate privileges can view sensitive BI Publisher reports embedded within Oracle Analytics Cloud dashboards. Which security model should be implemented?
Answer: A
Explanation:
Embedded Publisher reports remain protected by Oracle Analytics and Publisher authorization controls.
Authentication establishes who the user is, but access to the underlying Publisher content must additionally be governed through application roles, functional privileges, and Catalog permissions .
Oracle Analytics allows administrators to assign users and groups to application roles and then grant those roles access to Catalog objects. Publisher also defines functional permissions such as running reports, developing reports, scheduling reports, and accessing output. Oracle's administration guidance makes an important distinction: possession of a functional role does not by itself grant access to specific Catalog objects; the appropriate Catalog permissions must also be assigned.
This is particularly important for reports embedded in dashboards. Securing only the dashboard page isn't sufficient protection for the underlying sensitive Publisher object. Database authentication alone likewise does not implement the complete analytics-content authorization model. Disabling cache doesn't establish access control.
Therefore, the appropriate solution is role-based access combined with Publisher Catalog security , ensuring that only authenticated and authorized users can access the sensitive embedded reports.
Reference Topic: Managing and Securing Oracle Analytics Publisher - Application Roles, Functional Privileges, and Catalog Security
NEW QUESTION # 49
A global enterprise is implementing Oracle Analytics Cloud and wants executives to view the same dashboard while automatically seeing only data for their own business unit. Which implementation best follows Oracle best practices?
Answer: A
Explanation:
The recommended architecture is to maintain a single governed dashboard and enforce data visibility through application roles and row-level security in the semantic model . Oracle Analytics allows semantic- model data filters to be assigned to specific application roles. When a user queries an object protected by those filters, Oracle Analytics incorporates the applicable security predicates into the generated query, restricting results to the rows that user's roles are authorized to access.
For example, executives can all open the same Revenue dashboard while a Business Unit data filter automatically restricts each executive to the appropriate organizational data. This approach centralizes dashboard maintenance and security policy while avoiding duplicated content.
Dashboard prompts are useful for interactive filtering, but user-controlled prompts are not a substitute for authorization. Separate dashboards or subject areas for every executive create unnecessary maintenance and introduce the risk of inconsistent logic.
Oracle specifically recommends applying data filters to application roles rather than individual users for scalable row-level security. Therefore, C is the correct governed implementation.
Reference Topic: Managing Administration, Security, and Performance - Application Roles and Row- Level Security
NEW QUESTION # 50
Which Oracle Analytics Cloud capability best differentiates governed analytics from purely self-service analytics?
Answer: D
Explanation:
The defining characteristic of governed analytics is the use of shared, centrally controlled metadata and business logic. Oracle Analytics semantic models provide a common layer where administrators and data modelers can define dimensions, measures, hierarchies, relationships, calculations, security rules, and business-oriented terminology once and expose those definitions consistently through subject areas.
This avoids a major risk inherent in unmanaged self-service analytics: different users creating different interpretations of the same metric. For example, if each department independently defines Revenue, Margin, Customer Count, or Fiscal Quarter, reports can produce contradictory business results even though they use the same underlying source data.
Governance doesn't mean administrators must create every report. Business users can still independently create analyses, dashboards, and other content against approved subject areas. Nor does governed analytics restrict users to spreadsheets. Instead, governance establishes a controlled semantic foundation while preserving analytical self-service.
Oracle specifically describes the semantic model as a business-oriented abstraction layer that incorporates semantics and governance rules. Therefore, shared metadata and centrally managed business definitions are what most clearly distinguish governed analytics, making D correct.
Reference Topic: Understanding Oracle Analytics Cloud - Governed Analytics and Shared Semantic Metadata
NEW QUESTION # 51
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