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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Using Layout Editor - Formatting and customizing reports - Creating Excel and eText templates - Using RTF Template Builder |
| Topic 2: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Creating and designing dashboards - Enhancing dashboards and briefing books - Dashboard prompts and pages |
| Topic 3: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Managing Oracle Analytics Publisher - Securing Publisher content and access |
| Topic 4: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating reports - Creating and managing data models |
| Topic 5: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Managing report data sources - Publisher administration - Report translations - Scheduling reports - Bursting and delivery |
| Topic 6: Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Topic 7: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Formatting data - Managing filters - Managing selection steps - Using prompts and variables |
| Topic 8: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Managing analytics content - Creating and managing views - Creating and managing analyses |
| Topic 9: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Performance and caching - Security and application roles - Administration |
| Topic 10: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Connecting to data sources - Migrating analytics artifacts |
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NEW QUESTION # 21
A report author needs a layout component that provides multidimensional data in tabular form. The component must support multiple measures and dimensions at all levels. Which layout component should the author insert?
Answer: B
Explanation:
A Pivot Table is the correct layout component because Oracle Analytics Publisher specifically defines it as a mechanism for presenting multidimensional information in tabular form. A pivot table can organize dimensions across rows and columns while simultaneously displaying multiple measures in the data region. It also supports subtotals at multiple hierarchy levels, making it appropriate for analytical reports where users need to compare measures across several dimensional intersections.
A Layout Grid is primarily a structural container used to position report components; it does not itself perform multidimensional analysis. A Gauge visualizes a measure relative to a scale or threshold and is unsuitable for displaying multiple dimensions in tabular form. Text Items provide static or dynamically generated textual information, while Lists are designed for repeated structured content rather than multidimensional cross- tabulation.
Oracle's Publisher documentation explicitly describes the Pivot Table as providing multidimensional data in tabular form and supporting multiple measures, dimensions, and subtotals at all levels. This directly matches every requirement in the scenario.
Reference Topic: Building and Formatting Reports Using Layout Editor and Template Builder - Pivot Tables and Layout Components
NEW QUESTION # 22
A dashboard author wants users to see a list of briefing books on a dashboard page. How should the author configure the dashboard page?
Answer: E
Explanation:
Oracle provides a specific Dashboard Builder procedure for displaying a list of briefing books . The briefing books should be stored in a catalog folder. The dashboard author then drags a Folder object from the Dashboard Objects pane into the required dashboard section and opens its properties. In Folder Properties , the author specifies the folder containing the briefing books.
At runtime, the Folder object presents the folder's available briefing books to authorized users. Oracle also allows the author to control whether the folder initially appears expanded.
The Add to Briefing Book option performs the opposite task: it adds dashboard-page or analysis content into a briefing book rather than displaying a collection of existing briefing books. Downloading individual PDF versions likewise doesn't create a dashboard-accessible list. Saved Customizations preserve dashboard state and prompt selections, not catalog-folder contents.
Oracle's documented workflow directly specifies: add a Folder object, open Folder Properties, and identify the folder containing the briefing books. Therefore, option A precisely implements the required dashboard behavior.
Reference Topic: Designing, Creating, and Enhancing Dashboards - Briefing Books and Folder Objects
NEW QUESTION # 23
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: A
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 # 24
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: D
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 # 25
While creating a data model in Oracle Analytics Publisher, a developer needs to retrieve data directly from an Oracle Database using a custom SQL statement. Which data set type should be used?
Answer: C
Explanation:
A SQL Query Data Set is the appropriate Publisher data-set type when a report data model must retrieve relational data by executing a custom SQL statement. In the Data Model Editor, the developer selects New Dataset # SQL Query , chooses the required configured data source, and then enters a Standard SQL statement or invokes Query Builder to construct the statement graphically.
Oracle Analytics Publisher supports SQL Query Data Sets against Oracle Database and other supported relational sources. The SQL can contain standard SELECT logic and can also be extended with supported bind variables and other Publisher capabilities where required. This gives the developer direct control over the data retrieved for the report.
An XML Data Set consumes XML-based data rather than running relational SQL. An Excel Data Set retrieves spreadsheet content, while generic file-based options don't provide direct execution of a custom Oracle Database SQL statement.
Oracle's official documentation explicitly instructs developers to create an SQL Query dataset for this requirement. Therefore, C directly matches the described data-access method.
Reference Topic: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher - SQL Query Data Sets
NEW QUESTION # 26
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