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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Using prompts and variables - Formatting data - Managing filters - Managing selection steps |
| Topic 2: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating reports - Creating and managing data models |
| Topic 3: Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Topic 4: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Connecting to data sources - Migrating analytics artifacts |
| Topic 5: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Using RTF Template Builder - Formatting and customizing reports - Creating Excel and eText templates - Using Layout Editor |
| Topic 6: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Creating and designing dashboards - Enhancing dashboards and briefing books - Dashboard prompts and pages |
| Topic 7: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Creating and managing views - Creating and managing analyses - Managing analytics content |
| Topic 8: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Managing Oracle Analytics Publisher - Securing Publisher content and access |
| Topic 9: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Performance and caching - Security and application roles - Administration |
| Topic 10: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Scheduling reports - Publisher administration - Bursting and delivery - Managing report data sources - Report translations |
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NEW QUESTION # 78
A business user wants to compare current-quarter sales against only the top five performing product categories. Which feature best supports this requirement?
Answer: A
Explanation:
A Top N selection/filtering operation is the feature designed to retain only the highest-performing members according to a selected measure. In this case, Product Category is the dimension and current-quarter Sales is the measure used to rank the categories. Configuring the analytical selection to retain the top five categories produces exactly the required comparison population.
Oracle Analytics supports both selection-step member refinement and explicit Top/Bottom N filtering capabilities. The current Oracle Analytics documentation includes Top N examples that identify the highest attribute values based on a measure, which is precisely the analytical pattern in this question.
The important concept is that the ranking is based on the measure rather than visual styling. Conditional Formatting could visually distinguish high or low Sales values but wouldn't restrict the result to five product categories. Repository Initialization Blocks initialize semantic-model variables and have no role in ranking members. Dashboard Page Style controls appearance and layout rather than result membership.
Therefore, Selection Step with Top N filtering is the best supplied answer because it limits the displayed product categories according to their current-quarter Sales ranking and retains only the five highest performers.
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Top N Analysis
NEW QUESTION # 79
An author repeatedly uses the same state filter in multiple analyses and wants to reuse the filter. What should the author do?
Answer: C
Explanation:
The author should save the filter as a named filter in the catalog . Oracle Analytics distinguishes between inline filters and named filters. An inline filter belongs to one specific analysis, whereas a named filter is stored independently in the Oracle Analytics Catalog and can subsequently be referenced by multiple compatible analyses.
This is particularly useful for centrally reused business criteria. For example, an organization might create a named filter representing a specific State, Quarter, business unit, or product group. Report authors can then apply that saved filter to multiple analyses rather than recreate the filter definition repeatedly. Oracle also notes that when a named filter is edited and saved, changes can propagate wherever the named filter is referenced, improving consistency and maintainability.
Changing AND/OR grouping merely modifies logical relationships between existing filters and doesn't make the filter independently reusable. Drilling changes the current analytical detail level. A dashboard prompt provides runtime filtering but isn't required simply to reuse the same predetermined filter definition.
Therefore, the appropriate reusable object is a Named Filter saved in the Catalog .
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Named Filters
NEW QUESTION # 80
An administrator has replicated on-premises data to a cloud database and is updating RPD connection pools before migration. Which two connection-pool settings or checks should the administrator apply?
Answer: A,F
Explanation:
Before migrating a semantic model to Oracle Analytics Cloud, database connection information in every relevant connection pool must be updated for the cloud database. Oracle specifically requires the Call Interface to be Oracle Call Interface (OCI) for Oracle Database connections. In addition, for Oracle Analytics Cloud migration scenarios, the Data Source Name must contain the full connect string for the database containing the replicated data.
Oracle's current semantic-model migration guidance is explicit that a net service name isn't sufficient in this OAC scenario. This differs from some Oracle Analytics Server deployments where tnsnames.ora aliases can be supported. The cloud migration workflow therefore requires administrators to examine each connection pool, not merely the first connection associated with a database object.
ODBC isn't the recommended Oracle Database interface for this configuration, and restarting the BI Server after every individual connection-pool modification isn't part of the specified preparation procedure.
Thus, the required combination is OCI as the call interface and the complete database connect string as the Data Source Name , exactly matching D and E.
Reference Topic: Connecting to Data Sources and Migrating Artifacts - Preparing Semantic Models
/RPDs for Oracle Analytics Cloud
NEW QUESTION # 81
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: E
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 # 82
A developer is using Query Builder to create a SQL query from multiple tables. Which two actions are used to define the query in Query Builder?
Answer: B,D
Explanation:
Query Builder provides a graphical mechanism for defining relational SQL data sets. When multiple tables are involved, the developer must first establish the logical relationship between them. Typically, this means creating a join using matching columns , such as a parent table's primary key and a child table's corresponding foreign key.
After the tables and relationships are established, the required output fields are selected by choosing the check boxes beside the column names in Query Builder's design interface. Those selected fields become part of the generated SELECT list. Oracle's Query Builder documentation and examples show precisely this pattern:
create the relationship between tables, select the desired columns, optionally define conditions and sorting, and then save the generated SQL.
A report definition doesn't need to be created before building the query. Dashboard definitions are unrelated to Publisher SQL Query datasets. Sample-data generation occurs after the query has been defined sufficiently to execute, and parameters are optional rather than prerequisites for creating table relationships.
Accordingly, the two essential query-definition operations are joining the related tables and selecting the required columns , making C and E correct.
Reference Topic: Exploring and Creating Reports and Data Models - Query Builder, Joins, and Column Selection
NEW QUESTION # 83
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