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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | - Securing Publisher content and access - Managing Oracle Analytics Publisher |
| Topic 2: Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | - Dashboard prompts and pages - Creating and designing dashboards - Enhancing dashboards and briefing books |
| Topic 3: Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | - Bursting and delivery - Scheduling reports - Report translations - Managing report data sources - Publisher administration |
| Topic 4: Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | - Administration - Security and application roles - Performance and caching |
| Topic 5: Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | - Formatting data - Using prompts and variables - Managing filters - Managing selection steps |
| Topic 6: Building and Formatting Reports Using Layout Editor and Template Builder | 15% | - Creating Excel and eText templates - Using Layout Editor - Using RTF Template Builder - Formatting and customizing reports |
| Topic 7: Understanding Oracle Analytics Cloud | 5% | - Oracle Analytics Cloud concepts and capabilities |
| Topic 8: Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | - Connecting to data sources - Migrating analytics artifacts |
| Topic 9: Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | - Creating reports - Creating and managing data models |
| Topic 10: Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | - Managing analytics content - Creating and managing views - Creating and managing analyses |
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NEW QUESTION # 15
A report needs to group Revenue values by item type and Per-Year-Month into four dynamic buckets and may need to return the bin names. Which function should the author use?
Answer: B
Explanation:
The BIN function is specifically designed to classify a numeric expression into a defined number of equal- width buckets. Oracle documents syntax in which a numeric expression is evaluated at a specified grain using the BY clause, followed by INTO n BINS. The function can return the bin number or one of the interval boundary values , making it appropriate when the analysis needs both dynamic bucketing and a usable representation of each bucket.
In this scenario, Revenue is the numeric measure, while item type and Per-Year-Month establish the required analytical grain. Specifying four bins therefore partitions Revenue values into four dynamically calculated ranges at that grain.
MSUM calculates a moving sum across rows; it doesn't classify values into buckets. PERIODROLLING performs time-series aggregation over a specified period. RANK returns relative ordering, while TOPN identifies the highest-ranked members. None of these functions creates equal-width numeric bins.
Therefore, BIN applied to Revenue at the required grain and configured for four bins directly satisfies the requirement. Oracle's function reference explicitly defines BIN for this purpose.
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Analysis Functions and BIN
NEW QUESTION # 16
A BI developer creates a reusable analysis that should be available to multiple departments while maintaining centralized security. Where should the analysis normally be stored?
Answer: D
Explanation:
A reusable enterprise analysis intended for multiple departments should normally be stored in a Shared Folder within the Oracle Analytics Catalog. Shared Folders are designed for analytics content that needs to be consumed collaboratively and governed through centrally managed permissions.
Oracle recommends storing shared analytics objects in Shared Folders and assigning appropriate access rights to users or application roles. Administrators can create a structured shared-folder hierarchy and configure folder-level permissions so that contained objects inherit the required access controls. This is substantially easier to govern than maintaining separate copies of an analysis for individual users or departments.
By contrast, My Folders/personal folders are intended for content belonging to an individual user and aren't the appropriate location for enterprise-wide reusable objects. Browser storage and temporary caches aren't catalog repositories and provide neither durable analytics-content management nor centralized authorization.
A Shared Folder therefore enables the same analysis to be maintained once while granting departments the appropriate read, modify, or other access rights through catalog security.
Accordingly, option A provides the appropriate combination of reuse, centralized management, and security .
Reference Topic: Managing and Creating Analyses, Views, and Content - Shared Catalog Folders
NEW QUESTION # 17
You created a product-type dashboard prompt and applied it to the dashboard. When a user applies the prompt, two reports refresh as expected but two others do not. What are two possible reasons for this?
Answer: C,F
Explanation:
A dashboard prompt can affect an embedded analysis only when the analysis is configured to accept the prompt's value. A protected filter deliberately prevents a dashboard prompt from overriding that filter.
Oracle describes protected versus unprotected filters specifically as a mechanism controlling whether dashboard prompt values can determine an analysis's results. Therefore, a protected filter is a direct explanation for one of the non-responsive reports.
The second issue is a mismatch between the prompt column formula and the analysis filter formula .
Prompt wiring depends on the relevant column identity and formula being compatible. If the analysis uses a modified formula while the prompt targets another formula, Oracle cannot automatically apply the prompt as intended.
By contrast, an Is Prompted filter is specifically intended to receive a prompt value and is therefore normally part of a working configuration. Cache expiration does not explain selective prompt incompatibility, and simply containing measure columns is not itself the documented cause.
The two failed analyses should therefore be inspected for protected filters and formula mismatches between their filtering expressions and the dashboard prompt.
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Dashboard Prompt Interaction
NEW QUESTION # 18
A company wants regional managers to access only their own dashboard while using a common dashboard design. Which Oracle Analytics feature provides the most maintainable solution?
Answer: C
Explanation:
The most maintainable approach is to retain a single dashboard design while using dashboard filtering together with security controls that ensure each manager sees only authorized data. Dashboard prompts can provide a common interactive filtering experience, while row-level or role-based security must enforce the actual access boundary.
Oracle Analytics supports application-role-based filtering so that different users opening shared analytics content see only the data applicable to their assigned role. Oracle also supports object and data-access permissions through application roles and semantic-model security. This means the organization can maintain one dashboard instead of creating separate copies for every regional manager.
It is important to distinguish functionality from security: a dashboard prompt alone isn't an authorization mechanism . The security filtering component must enforce which regional data each manager is entitled to access. The prompt can then support user interaction within that permitted dataset.
Duplicating dashboards increases maintenance effort and creates version drift. Separate subject areas for each individual manager are also unnecessarily complex, while static PDF exports eliminate interactive analytics.
Therefore, D is the maintainable architecture: one dashboard, shared interaction design, and centrally enforced security filtering .
Reference Topic: Designing, Creating, and Enhancing Dashboards - Shared Dashboard Design and Security Filtering
NEW QUESTION # 19
A security administrator wants to assign analytics privileges to multiple users without configuring permissions individually. What is the recommended approach?
Answer: D
Explanation:
The recommended Oracle Analytics security model is to manage permissions through Application Roles . An application role represents a set of permissions determining what its members can see and do in Oracle Analytics Cloud. Administrators can assign users, groups, and even other application roles as members, allowing authorization to be administered centrally.
This is considerably more scalable than granting permissions individually. For example, an administrator can create or use an application role for Finance Analysts, assign the required analytics privileges and content permissions to that role, and then add all qualifying users to it. When staffing changes occur, administrators modify membership rather than repeatedly redesigning permissions.
Oracle's current guidance explicitly states that it is a best practice to assign permissions through application roles. Predefined roles such as BI Content Author and BI Consumer provide standard capabilities, while user- defined application roles can be created for organization-specific requirements.
Separate catalogs and duplicate dashboards would create unnecessary management overhead. Database accounts don't replace Oracle Analytics application-layer authorization.
Therefore, assigning users to Application Roles is the correct scalable approach.
Reference Topic: Managing Administration, Security, and Performance - Application Roles
NEW QUESTION # 20
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