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| Section | Weight | Objectives |
|---|---|---|
| Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Managing filters - Managing selection steps - Using prompts and variables - Formatting data |
| Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Performance and caching - Administration - Security and application roles |
| Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating and managing data models - Creating reports |
| Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Creating and managing analyses - Managing analytics content - Creating and managing views |
| Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Formatting and customizing reports - Creating Excel and eText templates - Using Layout Editor - Using RTF Template Builder |
| Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Migrating analytics artifacts - Connecting to data sources |
| Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Creating and designing dashboards - Dashboard prompts and pages - Enhancing dashboards and briefing books |
| Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Securing Publisher content and access - Managing Oracle Analytics Publisher |
| Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Bursting and delivery - Scheduling reports - Managing report data sources - Report translations - Publisher administration |
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질문 # 12
Which Oracle Analytics Cloud capability best differentiates governed analytics from purely self-service analytics?
정답：B
설명：
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
질문 # 13
Which Oracle Analytics Cloud administrative feature allows scheduled execution and delivery of analyses or alerts when predefined conditions are met?
정답：C
설명：
Agents are the intended Oracle Analytics capability for automatically executing analytical content according to a schedule or business condition and then delivering the resulting information to users or configured destinations. An agent can run periodically, evaluate a condition, select analytical content, identify recipients, and determine delivery destinations.
For example, an agent can evaluate an analysis each morning and deliver an alert only when inventory drops below a defined threshold. Oracle's current Oracle Analytics Cloud interface increasingly uses the term Delivery for this functionality, but the underlying scheduled/conditional delivery framework is the same capability historically identified as Agents in Classic Analytics.
Selection Steps control which members appear in analysis results. Trellis Views provide repeated comparative visualizations. Subject Areas expose governed business data from the semantic model. None of those features performs condition-driven scheduled delivery.
There is an internal error in the uploaded source: the placement of its "Correct answer" marker makes Selection Steps appear keyed, while the source explanation explicitly says that Agents automate execution and distribution based on schedules or conditions . Oracle documentation supports Agents/Deliveries, so the verified answer is A .
Reference Topic: Managing Administration, Security, and Performance - Agents, Deliveries, Conditions, and Scheduling
질문 # 14
Which statement describes the purpose of Virtual Private Database (VPD) in a secure reporting approach?
정답：A
설명：
Oracle Virtual Private Database (VPD) implements fine-grained, database-level access control by dynamically restricting rows returned to a user. A VPD policy associates a policy function with a protected table, view, or synonym. When a SQL statement references that object, Oracle Database automatically applies the policy-generated predicate to the statement.
For example, a query that conceptually requests every row from a sales table can transparently become a query restricted to the current user's authorized sales region. This makes VPD particularly suitable for reporting environments where multiple users execute similar reports but must see different subsets of the underlying data.
Oracle Analytics Publisher can preserve user identity through proxy-authenticated connections, while the database's VPD policy performs the row-level enforcement. This is fundamentally stronger than filtering sensitive rows only after they have already been returned to Publisher.
Catalog permissions solve a different security problem: they determine who can access or modify report objects. Bursting creates personalized documents but doesn't constitute database row-level security.
Therefore, VPD's defining role in this scenario is database-enforced row-level security , making A correct.
Reference Topic: Managing and Securing Oracle Analytics Publisher - VPD and Row-Level Data Security
질문 # 15
A development team has completed new dashboards and BI Publisher reports. Before deploying them to production, they need a repeatable migration process that preserves dependencies and configuration. Which approach is recommended?
정답：C
질문 # 16
A designer creates a report directly from an Oracle Analytics Cloud subject area. The report includes calculations that depend on original column functions. Which risk should the designer consider?
정답：D
설명：
The principal risk is that COUNT DISTINCT, AVG, and similar calculations can produce unexpected or different results when Publisher receives data that has already been summarized by Oracle Analytics .
When a report is created directly against a subject area, the BI Server performs semantic-model processing and aggregation before delivering the result set to Publisher. Publisher therefore does not necessarily receive the original detailed rows required to reproduce certain aggregate calculations accurately.
Oracle specifically cautions that subtotals and totals for subject-area reports are based on data already summarized by the BI Server. Functions requiring access to the original column-level data-Oracle explicitly identifies count distinct and average -can consequently return different results when reapplied within Publisher.
A data model is not mandatory when directly creating a subject-area report; direct subject-area reporting is specifically supported. Hierarchical columns are also not required and, in fact, have limitations in Publisher subject-area reports. The Create Report guide can directly query a subject area without requiring an intermediary Publisher data model.
Therefore, designers must understand the grain and aggregation state of data received from the semantic layer before introducing additional aggregate calculations.
Reference Topic: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher - Subject Area Reports
질문 # 17
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