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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Report translations - Scheduling reports - Managing report data sources - Bursting and delivery - Publisher administration |
| Topic 2: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Creating and managing views - Managing analytics content - Creating and managing analyses |
| Topic 3: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Managing Oracle Analytics Publisher - Securing Publisher content and access |
| Topic 4: Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Topic 5: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating reports - Creating and managing data models |
| Topic 6: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Using prompts and variables - Managing selection steps - Formatting data - Managing filters |
| Topic 7: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Performance and caching - Administration - Security and application roles |
| Topic 8: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Dashboard prompts and pages - Enhancing dashboards and briefing books - Creating and designing dashboards |
| Topic 9: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Connecting to data sources - Migrating analytics artifacts |
| Topic 10: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Using RTF Template Builder - Using Layout Editor - Formatting and customizing reports - Creating Excel and eText templates |
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100. Frage
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?
Antwort: D
101. Frage
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?
Antwort: E
Begründung:
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
102. Frage
An author wants to combine results from two subject areas in an analysis and asks whether the Analysis Editor can create joins between subject areas. Which approach should the author use?
Antwort: D
Begründung:
When the objective is to stack separate result sets , the Analysis Editor supports set operations such as UNION, UNION ALL, INTERSECT, and DIFFERENCE . Oracle documents a specific Combine Results function that lets authors create criteria from another subject area and apply a set operator to the two query result sets.
Set operations, however, aren't relational join definitions. They combine compatible result sets and require matching numbers of columns and compatible data types. They don't create primary-key/foreign-key or other semantic relationships between subject areas.
Cross-subject-area relational behavior depends on the semantic model , including common dimensions, facts, and relationships defined for the participating subject areas. Oracle also supports cross-subject-area analyses using conformed dimensions, but those relationships derive from model metadata rather than a join created ad hoc through set-operation syntax.
Dashboard prompts simply provide runtime filtering and don't create data relationships. Likewise, adding a second query doesn't itself define semantic join logic.
Therefore, the accurate distinction is: use set operators when stacking compatible result sets; define and govern actual joins through the semantic model .
Reference Topic: Managing and Creating Analyses, Views, and Content - Combining Subject Areas and Set Operations
103. Frage
A dashboard designer wants users to choose a department once, with every analysis on the dashboard responding to that selection. What is the recommended implementation?
Antwort: C
Begründung:
A Dashboard Prompt combined with a Presentation Variable provides a centralized runtime control that can be reused by multiple analyses on the same dashboard. Oracle defines a presentation variable as a variable whose value is populated from a column prompt or variable prompt. Each time the user changes the prompt selection, Oracle updates the presentation variable with the newly selected value.
The dashboard analyses can reference that variable in their filters or expressions. Consequently, the user selects Department once, and all appropriately configured content responds using the same runtime value.
This avoids duplicating prompt logic within each individual analysis and improves maintainability.
Applying separate filters manually would require maintaining similar logic in every analysis. Creating distinct dashboards for each department creates unnecessary duplication and version-management overhead. Multiple analysis-level prompts would also produce a fragmented user experience when a single dashboard-level selection is required.
Oracle's documentation explicitly states that presentation variables can be created through prompts and that their values change when users make new prompt selections. Therefore, the recommended architecture is one Dashboard Prompt that sets a Presentation Variable consumed by the related analyses.
Reference Topic: Designing, Creating, and Enhancing Dashboards - Dashboard Prompts and Presentation Variables
104. Frage
An author creates an analysis that includes at least one hierarchical column and clicks the Results tab. What view is automatically created for the analysis?
Antwort: C
Begründung:
Oracle Analytics determines the default result view according to the types of columns included in the analysis. Oracle documentation states that when an analysis contains only attribute and measure columns, the Compound Layout initially contains a table . However, when the analysis contains at least one hierarchical column , Oracle automatically creates a pivot table view .
This behavior is intentional because a pivot table is designed to represent hierarchical structures effectively. It supports expansion and collapse of hierarchy members, multidimensional presentation, and hierarchical navigation in ways that a conventional flat table doesn't.
A trellis view is useful for repeated visual comparisons across dimensions but isn't automatically generated merely because a hierarchy is present. Graph and gauge views must generally be added explicitly when appropriate. Likewise, the statement that every analysis defaults to a table is incorrect because Oracle specifically distinguishes hierarchical analyses from analyses containing only attribute and measure columns.
Therefore, once the author selects Results for an analysis containing a hierarchical column, the default result visualization is a Pivot Table . This behavior is directly documented in Oracle's Analysis Results guidance.
Reference Topic: Managing and Creating Analyses, Views, and Content - Hierarchical Columns and Default Views
105. Frage
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