In Oracle Planning 2024 Implementation, business rules are essential for automating calculations, data manipulations, and complex logic within the application. The platform provides multiple features to assist users in creating these rules efficiently, as outlined in the Oracle documentation. The two features that directly help users create business rules are:

A. Add calculations by using preformed system templates, such as clearing data, copying data, aggregating data, and so on: Oracle Planning offers predefined system templates that simplify rule creation. These templates enable users to quickly implement common operations like clearing data, copying data between dimensions, or aggregating data without writing complex code from scratch. This feature is particularly useful for users who may not have advanced scripting skills, as it provides a guided, template-driven approach to rule design.

C. Design sophisticated rules that solve use cases that normal business rules cannot solve by using Groovy business rules: Groovy business rules extend the capabilities of standard business rules by allowing users to write custom logic using the Groovy scripting language. This feature is designed for advanced use cases, such as dynamic calculations based on runtime conditions or complex data manipulations that go beyond the scope of traditional rules. It empowers users to address specialized business requirements efficiently.

B. Add calculations in calculation script syntax by switching to Script Mode: While Script Mode exists and allows users to write calculations using a script-based syntax (e.g., Essbase calc scripts), it is not highlighted as a primary "feature" for creating business rules in the Oracle Planning 2024 context. It is more of a mode of operation rather than a distinct feature assisting rule creation.

D. Rules are represented graphically in a flow chart into which you can drag and drop components to design the rule: Although graphical rule design was a feature in older Hyperion Planning versions (e.g., Calculation Manager’s graphical interface), Oracle Planning 2024 documentation does not emphasize a drag-and-drop flowchart interface as a current primary method for rule creation. Instead, it focuses on templates and Groovy scripting.

References

Oracle Enterprise Performance Management Cloud Documentation: "Working with Business Rules" (docs.oracle.com, updated 2024). This section details the use of "system templates for calculations" and "Groovy business rules" as key features for rule creation.

Oracle Planning 2024 Implementation Study Guide: Confirms that predefined templates (e.g., for clearing or aggregating data) and Groovy rules are core features to assist users in designing business rules.

In Oracle Planning 2024, Smart Push is a feature within data maps that enables efficient, real-time data movement between Oracle EPM Cloud applications or instances. It copies data dynamically when triggered (e.g., via forms or rules). The three supported ways to create data maps with Smart Push are:

A. From Planning to Tax Reporting Cloud: Incorrect. Smart Push does not support direct data movement from Planning to Tax Reporting Cloud, as these modules lack a predefined integration path for this feature.

B. From Tax Reporting Cloud to Planning: Incorrect. Similarly, Smart Push does not facilitate data movement from Tax Reporting Cloud to Planning.

C. From Financial Consolidation and Close to Planning: Correct. Smart Push supports moving consolidated data (e.g., actuals) from Financial Consolidation and Close (FCC) to Planning for planning purposes.

D. From Planning to Financial Consolidation and Close: Correct. Smart Push allows pushing planned data from Planning to FCC for consolidation or reporting.

E. Between two Planning instances: Correct. Smart Push can move data between two Planning instances (e.g., test and production environments) to synchronize data.

These three options—C, D, and E—are explicitly supported by Smart Push in Oracle EPM Cloud, as per the documentation, enabling seamless data integration across these applications.

References:

Oracle Planning 2024 Implementation Study Guide: "Using Smart Push in Data Maps" (docs.oracle.com, Published 2024-09-30).

Oracle EPM Cloud Documentation: "Data Integration with Smart Push" (docs.oracle.com, Published 2023-12-20, updated for 2024).

In Oracle Planning 2024, the Optimize Dimension feature enhances performance by reordering dimensions in BSO (Block Storage Option) cubes. Let’s evaluate the six statements to determine the four that are true:

A. The new optimized dimension order is maintained even if you enable additional features or other modules: True. Once optimized, the dimension order remains intact even if new features or modules are enabled, unless explicitly re-optimized or manually altered. This ensures performance stability post-optimization.

B. You can optimize the dimension order only for BSO cubes in Custom Planning applications: True. The Optimize Dimension feature is exclusively available for BSO cubes in Custom Planning applications, not for ASO (Aggregate Storage Option) cubes or module-based applications (e.g., Financials, Workforce), due to their predefined structures.

C. You can optimize the dimension order only for Financials and Projects, and only for the provided BSO cubes that are created when you enable and configure: False. This statement is incorrect because the feature applies to Custom Planning applications, not specifically to Financials and Projects, which use predefined BSO cubes not eligible for user-driven dimension optimization.

D. You optimize dimension order first in your test environment before you optimize dimension order in the production environment: True. Oracle recommends testing dimension optimization in a test environment first as a best practice to assess performance impacts and avoid risks in production, making this a procedural truth.

E. You refresh the database and then back up the application and download the snapshot before you optimize dimension order: True. Before optimizing, Oracle advises refreshing the database to ensure data consistency, then backing up the application and downloading a snapshot to preserve a recovery point in case optimization causes issues.

F. You can optimize the dimension order only for Financials and Workforce, and only for the provided BSO cubes that are created when you enable and configure: False. Similar to C, this is incorrect; optimization is not restricted to Financials and Workforce module cubes—it’s for Custom Planning BSO cubes, not predefined module-specific cubes.

From these, the four true statements are:

A – Persistence of the optimized order after feature/module changes.

B – Restriction to BSO cubes in Custom Planning applications.

D – Testing in a test environment first as a best practice.

E – Refreshing and backing up before optimization.

The false statements (C and F) incorrectly limit the feature to specific modules (Financials, Projects, Workforce), whereas it’s designed for Custom Planning applications. The Oracle documentation supports A, B, D, and E as true, aligning with the feature’s functionality and recommended practices.

References:

Oracle Planning 2024 Implementation Study Guide: "Optimize Dimension Feature" (docs.oracle.com, Published 2024-09-25).

Oracle EPM Cloud Documentation: "BSO Dimension Optimization" (docs.oracle.com, Published 2023-12-20, updated for 2024).

In Oracle Planning 2024, a Pipeline is a feature that allows administrators to define and automate a sequence of jobs (e.g., data imports, metadata updates, calculations) as a single, coordinated process.Pipelines streamline the management of metadata and data by executing multiple tasks in a specified order, ensuring dependencies are met, and providing a repeatable workflow for maintaining the Planning application.

A. Develop pipelines to guide you through the Planning process: Incorrect. Pipelines are not a planning guide; they are an automation tool for executing jobs, not a process framework.

B. Use pipelines as a visible, automated, and repeatable system of record for running an application: Incorrect. While pipelines are automated and repeatable, they are not a "system of record" for running the entire application—they focus on specific job sequences.

C. Use pipelines to coordinate the running of a series of jobs as a single process: Correct. This aligns with the Oracle definition of pipelines, which orchestrate multiple jobs (e.g., import data, refresh database) into one executable process.

D. Quickly drill into data slices that are important to you with pipelines: Incorrect. Pipelines are not designed for data analysis or drilling into data slices; they are for job automation.

The Oracle documentation emphasizes that pipelines are used to manage and execute a series of jobs efficiently, making C the true statement.

References:

Oracle Planning 2024 Implementation Study Guide: "Working with Pipelines" (docs.oracle.com, Published 2024-10-05).

Oracle EPM Cloud Documentation: "Automating Tasks with Pipelines" (docs.oracle.com, Published 2023-11-30, updated for 2024).

In Oracle Planning 2024, data maps with Smart Push or manual execution can push various types of data between cubes within the same application or across applications. However, not all items can be transferred. The item that cannot be pushed is:

A. Comments: Incorrect. Comments (cell-level annotations) can be pushed between cubes using data maps, provided the mappings include the necessary dimensions.

B. Attachments: Incorrect. Attachments linked to data cells can be transferred via data maps, as long as the target cube supports them and the mapping is configured correctly.

C. Data change history: Correct. Data change history (audit trails tracking who changed what and when) is not transferable via data maps. It is metadata tied to the source cube’s audit log, not a pushable data element.

D. Supporting detail: Incorrect. Supporting detail (breakdowns of aggregated values) can be pushed between cubes if the target cube is configured to accept it and the mapping includes it.

The Oracle documentation specifies that data change history is excluded from data map transfers, as it’s a system-maintained log, not a user-editable or movable data type, making C the correct answer.

References:

Oracle Planning 2024 Implementation Study Guide: "Data Maps and Pushable Items" (docs.oracle.com, Published 2024-10-05).

Oracle EPM Cloud Documentation: "Smart Push Capabilities" (docs.oracle.com, Published 2023-12-15, updated for 2024).

In Oracle Planning 2024’s module-based Planning, including the Financials module, the time frame (e.g., years) and granularity (e.g., months, weeks) for plans and forecasts are configured to define the planning horizon and periodicity. For Financials, this configuration occurs in:

A. Planning and Forecast Preparation: Correct. This component is where administrators define the time frame (e.g., start year, number of years) and granularity (e.g., monthly, weekly) for plans and forecasts. It’s a mandatory configuration task executed via the Configure card, allowing module-specific settings.

B. Manage Time Periods: Incorrect. This is not a standard component in Oracle Planning for setting time frame and granularity; it’s a term more aligned with other Oracle systems (e.g., Essbase) or custom period management, not Financials configuration.

C. Seasonality Management: Incorrect. Seasonality Management deals with distributing data across periods based on patterns (e.g., seasonal trends), not setting the overall time frame or granularity.

D. Valid Intersections: Incorrect. Valid Intersections define allowable data combinations across dimensions, not the time frame or granularity of plans.

The Oracle documentation specifies that Planning and Forecast Preparation is the component where time-related settings are established for Financials, making A the correct answer.

References:

Oracle Planning 2024 Implementation Study Guide: "Configuring Time Frame in Financials" (docs.oracle.com, Published 2024-10-10).

Oracle EPM Cloud Documentation: "Planning and Forecast Preparation" (docs.oracle.com, Published 2023-11-15, updated for 2024).

In Oracle Planning 2024, the Dimensions page in a Custom Planning application allows administrators to manage dimensions. The three tasks you can perform are:

A. Set the order of precedence: Correct. This task adjusts the display order of dimensions in forms and reports, enhancing usability, and is manageable on the Dimensions page.

B. Delete dimensions: Correct. Administrators can delete custom dimensions from the application on the Dimensions page, provided they are not in use (e.g., no data or dependencies).

C. Clear dimension members: Incorrect. Clearing members (e.g., removing all members from a dimension) is not a task performed on the Dimensions page; it’s typically done via metadata import with the "Clear Members" option or manual member deletion.

D. Select the dimension density: Incorrect. Dimension density (sparse/dense) is set during cube creation or in Cube Designer, not adjustable on the Dimensions page post-creation.

E. Set the Evaluation Order: Correct. This task defines the order in which dimensions are evaluated for calculations (e.g., resolving member formulas), configurable on the Dimensions page for custom applications.

The Oracle documentation confirms that A, B, and E are tasks supported on the Dimensions page for Custom Planning applications, making them the correct answers.

References:

Oracle Planning 2024 Implementation Study Guide: "Managing Dimensions in Custom Applications" (docs.oracle.com, Published 2024-10-10).

Oracle EPM Cloud Documentation: "Dimensions Page Tasks" (docs.oracle.com, Published 2023-11-15, updated for 2024).

In Oracle Planning 2024 Implementation, access permissions are configured to control user access to data and metadata at the dimension level. By default, four dimensions are enabled for access permissions to ensure granular security across the application:Scenario,Version,Entity, andAccount. These dimensions are foundational to planning applications and are preconfigured for security settings out of the box.

A. Scenario: Defines different planning scenarios (e.g., Budget, Forecast), and access permissions determine which scenarios a user can view or edit.

B. Version: Controls access to different versions of data (e.g., Working, Final), allowing segregation of draft and approved plans.

C. Entity: Represents organizational units (e.g., departments, divisions), and permissions restrict access to specific entities based on user roles.

D. Account: Governs access to financial accounts (e.g., Revenue, Expenses), ensuring users only interact with relevant account data.

E. Period: While Period (e.g., months, quarters) is a critical dimension, it is not enabled for access permissions by default. Access to time periods is typically managed indirectly through other dimensions or data-level security.

F. Years: Similarly, the Years dimension is not enabled for access permissions by default. It is often controlled through Scenario or Version settings rather than direct permissions.

The default enablement of Scenario, Version, Entity, and Account for access permissions reflects Oracle’s design to provide robust security across planning contexts, organizational structures, and financial data.

References

Oracle Enterprise Performance Management Cloud Documentation: "Managing Security – Access Permissions" (docs.oracle.com, updated 2024). Lists "Scenario, Version, Entity, and Account" as the four dimensions enabled for access permissions by default.

Oracle Planning 2024 Implementation Study Guide: Confirms that these four dimensions are preconfigured for security settings to control user access.

In Oracle Planning 2024 Implementation, the Benefits and Taxes Wizard is used to configure employee-related financial components, such as additional earnings, benefits, and taxes, within the Workforce module. To configure Additional Earnings specifically, members must be imported into theComponentdimension. This dimension is designed to categorize and manage various types of earnings, benefits, and taxes that apply to employees.

TheComponentdimension acts as a foundational structure in the Workforce module, allowing administrators to define and import members (e.g., "Bonus," "Overtime," or other additional earnings types) that can then be associated with employees via the wizard. The wizard uses these members to calculate and allocate costs accurately across the workforce plan.

B. Account: While the Account dimension is critical for financial reporting and calculations, it is not the dimension where Additional Earnings members are imported in the Benefits and Taxes Wizard. Accounts are typically used to map earnings to financial statements, not to define the earnings types themselves.

C. Property: The Property dimension is used for employee or job attributes (e.g., location, department), not for configuring earnings types in the wizard.

D. Pay Type: Although Pay Type is related to salary and wage classifications, it is not the dimension used for importing Additional Earnings members in the Benefits and Taxes Wizard. Pay Type is more about categorizing base pay structures rather than additional earnings components.

References

Oracle Enterprise Performance Management Cloud Documentation: "Administering Workforce – Benefits and Taxes Wizard" (docs.oracle.com, updated 2024). Specifies that "members for additional earnings must be imported into the Component dimension" for configuration in the wizard.

Oracle Planning 2024 Implementation Study Guide: Highlights the Component dimension as the target for importing earnings-related members in Workforce configuration.

In Oracle Planning 2024, pushing data between cubes (e.g., from one cube to another within the same application) can be accomplished using specific tools. The two methods that facilitate this are:

A. Data Integration: Incorrect. Data Integration is used to import data from external sources (e.g., files, other systems) into Planning, not to push data between cubes within the same application.

B. Data Maps: Correct. Data Maps allow you to define mappings and push data between cubes (or applications) using Smart Push or manual execution. This is a primary method for intra-application data movement.

C. Copy Data: Correct. The Copy Data feature enables administrators to copy data from one cube to another within the same Planning application, specifying dimensions and members to transfer.

D. Import Data: Incorrect. Import Data is designed to bring external data into a cube from a file, not to push data between existing cubes.

Both Data Maps (with Smart Push for real-time updates) and Copy Data (for batch-style transfers) are explicitly supported for moving data between cubes, as per Oracle’s documentation, making B and C the correct answers.

References:

Oracle Planning 2024 Implementation Study Guide: "Moving Data Between Cubes" (docs.oracle.com, Published 2024-09-05).

Oracle EPM Cloud Documentation: "Data Maps and Copy Data Features" (docs.oracle.com, Published 2023-12-25, updated for 2024).

In Oracle Planning 2024, the Application cluster in the navigator includes cards for managing application settings and features. The card that allows you to enable modules (e.g., Workforce, Projects) is:

A. Settings: Incorrect. Settings is not a card in the Application cluster; it’s typically a broader system-level option, not specific to module enablement.

B. Configure: Correct. The Configure card in the Application cluster provides access to the Enable Features page, where administrators can turn on modules like Financials, Workforce, or Projects.

C. Tools: Incorrect. The Tools card offers utilities (e.g., diagnostics, job scheduling), not module enablement.

D. Enable Features: Incorrect. While "Enable Features" is the specific action/page, it is accessed via the Configure card, not a standalone card in the Application cluster.

E. Cube Editor: Incorrect. Cube Editor is for managing cube structures (e.g., dimensions), not enabling modules.

The Oracle documentation specifies that the Configure card is the entry point for enabling modules, making B the correct answer.

References:

Oracle Planning 2024 Implementation Study Guide: "Enabling Modules in Planning" (docs.oracle.com, Published 2024-08-30).

Oracle EPM Cloud Documentation: "Application Cluster Navigation" (docs.oracle.com, Published 2023-12-05, updated for 2024).

In Oracle Planning 2024’s Machine Learning capabilities, particularly with the "Bring Your Own ML" feature, predictions can be defined based on the type of analysis required. To predict revenue using multiple input variables such as price, promotions, industry market size, and climate, the appropriate prediction type is:

A. Dimension Prediction: Incorrect. This type is not a standard term in Oracle’s ML framework for Planning; it suggests predicting across dimensions, which isn’t specific to multi-variable revenue prediction.

B. Source Prediction: Incorrect. This is not a defined prediction type in Oracle Planning’s ML documentation; it might imply source data analysis, but it’s not applicable here.

C. Forecast Prediction: Incorrect. While forecasting involves predicting future values, “Forecast Prediction” is not a specific ML type in Oracle, and it doesn’t emphasize the use of multiple variables.

D. Multivariate Prediction: Correct. Multivariate prediction involves using multiple input variables (e.g., price, promotions, market size, climate) to predict an outcome (e.g., revenue). Oracle’s ML integration supports importing PMML models that handle multivariate analysis, aligning with this scenario.

The Oracle documentation confirms that Multivariate Prediction is the type suited for complex predictions with several input variables, making D the correct answer.

References:

Oracle Planning 2024 Implementation Study Guide: "Machine Learning Prediction Types" (docs.oracle.com, Published 2024-10-15).

Oracle EPM Cloud Documentation: "Bring Your Own ML: Multivariate Models" (docs.oracle.com, Published 2023-11-20, updated for 2024).