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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Understanding Oracle Analytics Cloud | 5% | |
| Topic 2: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | |
| Topic 3: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | |
| Topic 4: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | |
| Topic 5: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | |
| Topic 6: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | |
| Topic 7: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | |
| Topic 8: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | |
| Topic 9: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | |
| Topic 10: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% |
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NEW QUESTION # 73
What happens when a user drills on an attribute column in the Analysis Editor?
Answer: C
Explanation:
Drilling on an attribute column performs what Oracle describes as a filter drill . When the user clicks a drillable attribute value, Oracle adds the next lower level to the displayed analysis and creates a filter corresponding to the member on which the user drilled.
Oracle's documentation states that drilling in an attribute column affects all relevant views. After the value is clicked, a column is added to the analysis and a filter is automatically created and listed on the Criteria tab . This distinguishes attribute-column drilling from drilling in hierarchical columns, where expanding or collapsing hierarchy members generally affects only the particular hierarchy view without creating the same analysis-wide filter drill behavior.
The drill operation therefore modifies the analytical context; the underlying criteria don't simply remain unchanged. Oracle also doesn't automatically save the resulting drill filter as a reusable named filter, nor does a drill operation create a dashboard prompt. Those are separate authoring operations.
Consequently, the specific outcome described by Oracle is exactly option A: drilling an attribute column automatically introduces the corresponding filter and adds the lower-level column to the analysis criteria.
Reference Topic: Managing and Creating Analyses, Views, and Content - Drilling in Analysis Results
NEW QUESTION # 74
Which Oracle Analytics Cloud capability best differentiates governed analytics from purely self-service analytics?
Answer: C
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 # 75
A report designer needs to display sales performance by Region, Product Category, and Quarter in a highly interactive visual comparison. Which view is most appropriate?
Answer: D
Explanation:
A Trellis View is the most appropriate visualization for comparing the same measure across multiple dimensional categories. A trellis displays a series of related visualizations in a grid, allowing users to compare equivalent graphical structures across dimension members.
For example, the designer could use Region or Product Category as an outer-edge dimension and Quarter or another analytical dimension within the repeated visualizations. Because every trellis cell follows a consistent graphical framework, differences in sales performance become easier to identify across categories.
Oracle distinguishes between Simple Trellis and Advanced Trellis use cases. Oracle recommends Simple Trellis for general comparisons and Advanced Trellis when analyzing trends. The documentation also advises controlling dimensional density so that each repeated graph remains readable.
A Narrative View renders textual descriptions generated from query results and isn't optimized for comparative multidimensional visualization. A static table can present all values but provides less immediate visual comparison. A KPI is generally intended to summarize performance against targets rather than display a repeated multidimensional comparison across Region, Product Category, and Quarter.
Therefore, Trellis View best satisfies the scenario.
Reference Topic: Managing and Creating Analyses, Views, and Content - Trellis Views
NEW QUESTION # 76
An administrator wants BI Content Authors to have the Save Content with HTML Markup privilege. How should the administrator configure this privilege?
Answer: D
Explanation:
Oracle Analytics functional privileges are granted through Manage Privileges . To allow members of the BI Content Author application role to save analytics content containing HTML markup, the administrator opens the Classic Administration interface, selects Manage Privileges , locates Save Content with HTML Markup
, and grants that privilege to the required application role.
This privilege is security-sensitive. Oracle Analytics protects Presentation Services against cross-site scripting by default, and saving content flagged as HTML is restricted unless the relevant privilege and system configuration permit it. Granting the privilege to an application role provides centralized administration because users inherit the capability through role membership rather than requiring individual privilege assignments.
Manage Sessions is used for user-session monitoring and query diagnostics; changing log level doesn't grant content-authoring privileges. Adding users to BI Content Author alone doesn't automatically grant this particular privilege if the role hasn't been assigned it. Catalog Manager handles catalog maintenance rather than functional privilege administration.
Consequently, the correct configuration path is Administration # Manage Privileges # Save Content with HTML Markup # BI Content Author .
Reference Topic: Managing Administration, Security, and Performance - Manage Privileges and HTML Content Security
NEW QUESTION # 77
An analyst wants to highlight sales values above target in green and values below target in red without changing the underlying data. Which feature should be used?
Answer: B
Explanation:
Conditional Formatting is specifically designed to modify the visual representation of data when defined conditions are satisfied while leaving the underlying values unchanged. The analyst can establish rules such as Sales greater than or equal to Target and apply one format, while values below Target receive a different format.
Oracle Analytics supports conditional rules based on measures, attributes, thresholds, percentages, and expressions. Formatting can include font characteristics, cell presentation, images, backgrounds, and visualization-specific properties. Oracle's examples include stoplight-style formatting in which low, medium, and high values receive different visual treatments.
This functionality affects presentation only; it doesn't alter the source Sales values or change the actual calculation. That directly satisfies the requirement.
A Repository Variable stores centrally maintained values and isn't itself a visualization rule. Selection Steps determine which members appear after query aggregation. A Subject Area Filter limits the data returned or made available rather than simply changing its appearance.
Consequently, the appropriate feature for showing above-target values in green and below-target values in red is Conditional Formatting , making A correct.
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Conditional Formatting
NEW QUESTION # 78
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