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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Creating Excel and eText templates - Using RTF Template Builder - Formatting and customizing reports - Using Layout Editor |
| Topic 2: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Migrating analytics artifacts - Connecting to data sources |
| Topic 3: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Publisher administration - Report translations - Bursting and delivery - Managing report data sources - Scheduling reports |
| Topic 4: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Dashboard prompts and pages - Enhancing dashboards and briefing books - Creating and designing dashboards |
| Topic 5: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Managing Oracle Analytics Publisher - Securing Publisher content and access |
| Topic 6: Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Topic 7: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Managing analytics content - Creating and managing analyses - Creating and managing views |
| Topic 8: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating reports - Creating and managing data models |
| Topic 9: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Performance and caching - Administration - Security and application roles |
| Topic 10: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Using prompts and variables - Managing filters - Managing selection steps - Formatting data |
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29. Frage
The administrator has navigated to the Console page and clicked Search Index. Which three items can be included in the index?
Antwort: A,B,D
Begründung:
The correct selections are Shared Folders, User Folders, and Data Models . Oracle Analytics provides search indexing for two broad categories: data-model content and catalog content . Data-model indexing controls whether semantic-model metadata-and optionally permitted data values-is indexed. Catalog indexing crawls analytics objects stored within catalog folders.
Oracle's current documentation explicitly states that the automatic catalog crawl indexes both user folders and shared folders . Administrators can exclude User Folders by clearing the Index User Folders option, which confirms that User Folders are a configurable indexed category. Oracle separately provides the Data Model tab for configuring semantic-model search indexing.
"Content Folder" is not the equivalent third selectable category in this question; catalog content is indexed through the Catalog configuration, which includes user and shared folders. Templates and "Dashboards Only" are likewise not the three high-level choices represented by the documented Search Index configuration.
Correction: the uploaded document marks Shared Folders, Data Models, and Content Folder. That key conflicts with Oracle's documented Search Index behavior. The verified answer is A, C, D .
Reference Topic: Managing Administration, Security, and Performance - Search Indexing
30. Frage
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?
Antwort: C,D
Begründung:
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
31. Frage
A scheduled report job uses a schedule trigger. The SQL query in the trigger returns no data when the job is scheduled to run. What is the result?
Antwort: E
Begründung:
The scheduled job instance is skipped . Oracle Analytics Publisher defines a Schedule Trigger as a SQL query that is executed when the scheduled report job is triggered, before the report itself runs. The returned result determines whether the execution condition has been satisfied.
Oracle states explicitly that if the trigger SQL returns data , the associated report job executes. If the SQL query returns no data , the job instance is skipped. This mechanism allows report execution to depend on a business or technical condition. For example, a report could execute only after an ETL process has completed, only when transactions exceed a specified amount, or only when new records have appeared.
The trigger doesn't convert the job into a bursting job, nor does Publisher execute an empty report merely with a warning. The scheduled job definition also isn't deleted; only that execution instance is skipped. For recurring schedules, subsequent trigger evaluations can still occur according to the configured recurrence and retry behavior.
Therefore, a no-row result from the Schedule Trigger means its condition evaluated as not satisfied and the current job instance is skipped .
Reference Topic: Managing Report Scheduling, Data Sources, Administration, and Translations - Schedule Triggers
32. Frage
What happens when a user drills on an attribute column in the Analysis Editor?
Antwort: A
Begründung:
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
33. Frage
Which action creates a reusable calculated metric that remains available within the current analysis?
Antwort: D
Begründung:
Adding a Calculated Column allows an analysis author to derive a new analytical value from existing columns or expressions without changing the underlying physical source data. The calculation becomes part of the current analytical definition and can be referenced throughout the analysis where supported.
Calculated expressions are useful for metrics such as profit percentage, variance, adjusted revenue, unit price, ratios, and other values derived from existing measures or attributes. This provides flexibility at the content- authoring layer while leaving centrally governed semantic-model objects unchanged.
The scope described in the question is important: the calculation must remain reusable within the current analysis . If the organization needed the metric governed and reusable across many analyses, defining the calculation centrally in the semantic model would normally provide stronger enterprise consistency.
A Dashboard Prompt supplies runtime values and filtering rather than creating calculated metrics. BAR files are migration artifacts and don't constitute an analysis calculation mechanism. Application Roles control authorization and permissions.
Therefore, among the available choices, Adding a Calculated Column is the function that creates the required derived metric in the analysis. The uploaded question explicitly associates this behavior with a calculated column.
Reference Topic: Managing and Creating Analyses, Views, and Content - Calculated Columns and Derived Metrics
34. Frage
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