1z0-1080-25 Oracle Planning 2025 Implementation Professional Questions and Answers

In Oracle Planning 2024, configuring Insights with Auto Predict allows users to analyze past and predicted data to uncover patterns and insights. Oracle provides specific guidelines to ensure effective implementation:

A. For future data, create a new insight by leveraging templates that include insight definitions: Incorrect. While templates can be used to set up Insights, this is not a specific Oracle guideline for implementing Auto Predict. Auto Predict relies on historical data and predictive algorithms, not predefined insight templates for future data.

B. For historical data, there should be at least twice the amount of historical data as the number of prediction periods: Correct. Oracle recommends having sufficient historical data—specifically, at least twice the number of periods you intend to predict—to ensure the accuracy of Auto Predict’s machine learning algorithms. For example, predicting 12 months requires at least 24 months of historical data.

C. For historical data, create the Insights job using the lowest level of Period members possible so that the greatest amount of historical data can be used: Incorrect. While granularity matters, Oracle does not mandate using the lowest level of Period members (e.g., days instead of months) as a guideline. The focus is on the quantity of historical data, not necessarily the lowest level of aggregation.

D. For future data, first run predictions in a test environment to ensure there is no impact on production data: Correct. Oracle advises testing Auto Predict in a non-production environment to validate results and avoid unintended impacts on live data, aligning with best practices for predictive analytics deployment.

The two guidelines—B and D—are explicitly outlined in Oracle’s documentation for Insights and Auto Predict to ensure reliable predictions and safe implementation.

In Oracle Planning 2024’s Workforce module, Merit-Based Planning involves planning salary increases or adjustments based on employee performance (merit). To perform this, you need workforce data at a level of granularity that includes individual employee details. The two levels required are:

A. Merit: Incorrect. "Merit" is not a granularity level; it’s a planning concept or assumption applied to employee data, not a structural level of detail.

B. Employee and Job: Correct. This level combines employee-specific data (e.g., individual identity) with job-specific data (e.g., role, grade), enabling merit-based adjustments tailored to both the person and their position.

C. Job: Incorrect. Job-level granularity (e.g., aggregated data for a role) lacks individual employee details, which are necessary for merit-based planning.

D. Employee: Correct. Employee-level granularity provides the individual data (e.g., current salary, performance rating) needed to calculate merit increases for specific employees.

Merit-Based Planning requires at least Employee-level detail, and often Employee and Job for more precise planning (e.g., tying merit to job roles or grades). The Oracle documentation confirms these as the key granularity levels for this functionality, making B and D the correct answers.

In Oracle Planning 2024, predefined roles in Cloud EPM determine user permissions. The requirement is for a role that allows a Planning user to create and administer Planning or Planning Modules and service components, as well as grant permissions to other users. Among the options:

A. System Administrator: Incorrect. This role exists in some Oracle systems but is not a Cloud EPM predefined role specific to Planning. It’s too broad and not aligned with EPM terminology.

B. Approvals Administrator: Incorrect. This role manages approval processes (e.g., workflows) but does not include creating/administering applications or granting permissions beyond approvals.

C. Identity Role Administrator: Incorrect. While this role manages identity and access (e.g., assigning roles), it does not allow creating or administering Planning applications or service components.

D. Service Administrator: Correct. The Service Administrator role in Cloud EPM allows users to create and manage Planning applications, configure modules and service components (e.g., forms, rules), and assign permissions to other users via access control.

The Service Administrator role is the highest-level predefined role in Oracle EPM Cloud for Planning, encompassing application management and user permission assignments, making it the correct choice.

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.

In Oracle Planning 2024 Implementation, infolets are a feature designed to provide users with quick, visual insights into critical business data. They are not full dashboards, task management tools, or process control mechanisms, but rather compact, high-level representations of aggregated information.

C. Infolets help you quickly analyze data and understand key business questions by presenting a visual overview of high-level, aggregated information: This statement accurately describes infolets. They are visual tiles or widgets that display summarized data (e.g., KPIs, trends) to help users grasp key business insights at a glance. Infolets are typically found on the home page or navigation clusters and are customizable to highlight specific metrics relevant to the user’s role or application.

A. Infolets are predefined dashboards that give you insight into the overall project financials and expense and revenue metrics: While infolets provide insights, they are not full "predefined dashboards." Dashboards are more comprehensive, whereas infolets offer concise, targeted views of data.

B. Infolets help you organize, track, and prioritize your workload: This describes task management or navigation features (e.g., task lists), not infolets, which focus on data visualization rather than workload management.

D. Infolets give business process designers control over how various roles or groups interact with a business process: Infolets are not about process design or role interaction; they are about displaying data, not controlling processes.

E. Infolets are a form type that provides flexible row management where dimension and member row cells and all data cells are unprotected: Infolets are not a form type; they are separate from forms and focus on visualization, not data entry or row management.

References

Oracle Enterprise Performance Management Cloud Documentation: "Using Infolets" (docs.oracle.com, updated 2024). Describes infolets as "visual overviews of high-level, aggregated information to quickly analyze data and answer business questions."

Oracle Planning 2024 Implementation Study Guide: Defines infolets as tools for presenting summarized data visually for quick analysis.

In Oracle Planning 2024, scheduling jobs such as a weekly data import is managed through the Jobs interface, which provides options for automation, monitoring, and notifications. Let’s evaluate the provided statements to identify the two that are true:

A. You can check the execution status of a job only if it completed: This is false. The Jobs console in Oracle EPM allows users to check the status of a job (e.g., Running, Completed, Failed) at any time, not just after completion. Real-time monitoring is a key feature.

B. You can set the daily maintenance time when scheduling cloning environment jobs: This is false. Daily maintenance time is a system-wide setting controlled by administrators via Application Settings, not something adjustable when scheduling specific jobs like cloning or data imports.

C. You can set to receive notifications when the job has completed: This is true. When scheduling a job (e.g., Import Data), users can enable email notifications to be alerted upon job completion, success, or failure, enhancing job management.

D. You can schedule an Import Data job to run later at intervals: This is true. The scheduling feature supports recurring jobs, such as weekly data imports, allowing users to define the start time and frequency (e.g., daily, weekly) for tasks like importing data from external sources.

E. You can delete that are currently processing: This is false. Jobs that are currently processing (i.e., in a "Running" state) cannot be deleted until they complete or fail, as per Oracle’s job management rules.

Thus, the two true statements are C and D, reflecting the flexibility of scheduling recurring Import Data jobs and receiving completion notifications, both of which are explicitly supported in Oracle Planning 2024.

In Oracle Planning 2024’s Strategic Modeling simulations, selecting a probability distribution for scenarios with fixed minimum and maximum values and a known most likely value (e.g., sales estimates, inventory, marketing costs) points to:

A. Beta PERT: Incorrect. Beta PERT uses min, max, and most likely values but requires more data to shape the curve accurately, making it less ideal with limited data.

B. Uniform: Incorrect. Uniform assumes equal probability between min and max, ignoring the most likely value, which doesn’t fit this scenario.

C. Triangular: Correct. The Triangular distribution uses minimum, maximum, and most likely values, making it simple and effective for limited data situations like sales or costs.

D. Normal: Incorrect. Normal requires mean and standard deviation, not just min, max, and most likely, and assumes more data availability.

E. Lognormal: Incorrect. Lognormal is skewed and suited for data with a positive range, requiring more statistical input than provided here.

The Oracle documentation recommends the Triangular distribution for its simplicity and suitability with limited data, making C the correct answer.

In Oracle Planning 2024, Service Administrators can use the Clone Snapshot feature to create an exact copy of the current application in a target environment. This feature automates all actions required for cloning, including removing the existing application and data in the target environment (if any) and replacing it with a snapshot of the source environment. The process involves exporting a snapshot from the source, deleting the target environment’s current application and data, and then importing and applying the snapshot to recreate the application identically.

A. Replicate Snapshot: This is incorrect because "Replicate Snapshot" is not a defined feature in Oracle Planning. Replication typically implies duplicating data without necessarily overwriting the target, which doesn’t align with the requirement of removing existing content.

B. Migration Export: This is incorrect because Migration Export only exports application artifacts (e.g., metadata, data) to a file for manual transfer or backup, but it does not automate the removal of the target environment’s content or the import process.

C. Clone Snapshot: This is correct. The Clone Snapshot feature, available under the Environment management tools, fully automates the cloning process, including deletion of the target environment’s application and data, followed by the recreation of the source application.

D. Migration Backup: This is incorrect because Migration Backup creates a backup file for recovery purposes but does not involve cloning or overwriting a target environment.

The Oracle Planning 2024 documentation specifies that Clone Snapshot is designed for such end-to-end automation, making it the ideal choice for Service Administrators to replicate an application across environments efficiently.

In Oracle Planning 2024’s Capital module, enabling Named Assets allows planning for specific, individually tracked assets (e.g., equipment, buildings) rather than generic asset categories. The two tasks you can perform when enabling Named Assets are:

A. Add the names of assets to plan at the detail level: Correct. When enabling Named Assets, you can specify the names of individual assets (e.g., “Truck A,” “Building 1”) to plan their costs, depreciation, and other details at a granular level.

B. Specify the likely number of tangible and intangible assets that you want to add in a planning cycle: Incorrect. While you estimate a maximum number of Named Assets during enablement, you don’t specify them by tangible/intangible categories—the distinction is managed later in asset planning, not at enablement.

C. Decrease the number of named assets after enabling Named Assets: Incorrect. Once Named Assets is enabled with a maximum number, you cannot decrease this limit directly; it requires reconfiguration or disabling/re-enabling the feature, which is not a standard task.

D. Increase the number of named assets after enabling Named Assets: Correct. After enablement, you can increase the maximum number of Named Assets (e.g., from 100 to 150) via the Configure card, allowing more assets to be added as needed.

The Oracle documentation confirms that A (adding asset names) and D (increasing the count post-enablement) are supported tasks for Named Assets, making them the correct answers.