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| Section | Weight | Objectives |
|---|---|---|
| Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | |
| Building and Formatting Reports Using Layout Editor and Template Builder | 15% | |
| Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | |
| Understanding Oracle Analytics Cloud | 5% | |
| Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | |
| Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | |
| Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | |
| Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | |
| Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | |
| Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% |
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NEW QUESTION # 56
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?
Answer: A
Explanation:
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
NEW QUESTION # 57
You have been tasked with building an analysis that requires data from two subject areas. How do you accomplish this?
Answer: C
Explanation:
Oracle Analytics supports cross-subject-area analyses , so the appropriate approach is to create the analysis using the primary subject area and then add another compatible or related subject area through the Analysis Editor.
Oracle's documented workflow starts by selecting one subject area and adding the initial analysis columns.
The author then uses Add/Remove Subject Areas in the Subject Areas pane to include another subject area and select the additional required columns. Where local dimensions are involved, Oracle recommends including an appropriate measure from each participating subject area so that the semantic model can resolve the query correctly.
The Analysis Editor is therefore capable of querying multiple subject areas when the semantic relationships support the requested combination. Modifying the semantic model simply to expose every required column in one subject area is unnecessary when compatible subject areas already exist. UNION is a set operation used for combining compatible result sets and is not the standard mechanism for selecting related columns across subject areas. MERGE and dashboard prompts likewise do not establish semantic relationships.
Thus, the supported workflow is to create one analysis and add the second related subject area.
Reference Topic: Managing and Creating Analyses, Views, and Content - Cross-Subject-Area Analyses
NEW QUESTION # 58
Which type of report is an example of the bursting feature in Pixel-Perfect Reporting?
Answer: A
NEW QUESTION # 59
Users report that frequently executed analyses are taking longer than expected even though the underlying data changes only once each day. Which feature can improve query response time?
Answer: B
Explanation:
Query caching is specifically designed to improve response time for repeated analytical queries. Oracle Analytics Cloud stores previously computed query results in a local query cache. When a later request can be satisfied from an existing cache entry, Oracle Analytics can return the precomputed result rather than execute another request against the underlying database.
This scenario is particularly suitable for caching because the underlying data changes only once per day. The administrator can therefore maintain a cache lifecycle aligned with the daily refresh process. After source data changes, relevant cache entries should be purged or refreshed to prevent stale results. Between refreshes, frequently repeated analyses can achieve significant performance improvements while reducing database processing, network traffic, and Oracle Analytics processing overhead.
Disabling caching would increase repeated source-system workload. Adding dashboard prompts doesn't inherently reduce query execution cost. Moving analyses into Personal Folders changes catalog organization and access, not query-processing efficiency.
Oracle explicitly states that query caching can dramatically improve query performance by satisfying subsequent requests without accessing back-end data sources. Therefore, D is correct.
Reference Topic: Managing Administration, Security, and Performance - Query Cache Management
NEW QUESTION # 60
An organization wants a dashboard page that displays executive KPIs, detailed trend charts, and supporting tables together in a single layout. Which dashboard capability should be used?
Answer: A
Explanation:
Compound Layout is the correct answer. Oracle Analytics defines a Compound Layout as a collection of multiple views of an analysis displayed together. Authors can position tables, pivot tables, graphs, narrative views, and other views within the same results layout. Oracle specifically states that multiple views can be combined and positioned anywhere within the Compound Layout.
This directly matches a requirement to show executive summary information, trend visualizations, and supporting detail together. An author can combine the relevant views and arrange them so consumers see different perspectives of the same analytical result set without moving between separate objects.
Guided Navigation serves a different purpose. It supports conditional navigation or conditionally displayed content based on analytical conditions; it isn't the layout container for simultaneously presenting multiple analytical views. Briefing Books capture dashboard content for offline or distributable consumption, while Action Links enable navigation or actions from analytical content.
The uploaded source contains an internal contradiction here: its answer marker identifies Guided Navigation
, but its own explanation describes Compound Layout . Oracle documentation confirms that A is the technically correct answer .
Reference Topic: Managing and Creating Analyses, Views, and Content - Compound Layouts
NEW QUESTION # 61
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