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Oracle 1z0-1080-24 Exam Syllabus Topics:

Topic	Details
Topic 1	Manage Rules: This section of the exam measures the skills of business rule developers and focuses on designing business rules and rulesets. It explains the benefits of Groovy Rules in enhancing performance and flexibility within Planning applications.
Topic 2	Set Up Planning Security: This section of the exam measures the skills of security administrators and focuses on provisioning users and groups. It includes assigning access permissions to artifacts and cells in Planning to ensure secure access to critical information.
Topic 3	Introduction to Strategic Modelling: This section of the exam measures the skills of strategic modelers and covers strategic modeling concepts. It includes setting up models, running simulations, and understanding their impact on decision-making processes.
Topic 4	Planning Overview: This section of the exam measures the skills of planning administrators and focuses on understanding the features of Planning applications. It includes setting up Planning and Freeform applications, managing dimensions, and explaining the impact of dimension hierarchies. It also covers configuring valid and invalid intersections and cell-level security.
Topic 5	Configure Intelligent Performance Management: This section of the exam measures the skills of machine learning specialists and focuses on configuring IPM components. It includes setting up machine learning models for predictive analytics within Planning applications.
Topic 6	Maintain Planning: This section of the exam measures the skills of system administrators and focuses on monitoring maintenance tasks for Planning applications. It includes scheduling jobs, managing EPM Automate for automation tasks, backing up data, migrating metadata, cloning environments, and maintaining system updates.
Topic 7	Introduction to Planning Modules: This section of the exam measures the skills of module planners and introduces Planning modules. It includes integrating modules, leveraging best practices for module planning, and configuring Financials, Workforce, Capital, and Projects.
Topic 8	Report on Planning Data: This section of the exam measures the skills of reporting analysts and covers creating reports on Planning data. It includes reporting on EPM data to provide insights into organizational performance.

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Oracle Planning 2024 Implementation Professional Sample Questions (Q50-Q55):

NEW QUESTION # 50
Which three types of revenue and expense assumptions drive data calculations in Projects?

A. Project rates
B. Working days and hours
C. Discount rates
D. Standard rates
E. Program mappings
F. Plan start year

Answer: A,B,D

Explanation:
In Oracle Planning 2024's Projects module, revenue and expense calculations are driven by specific assumptions that influence project financials. The three types of assumptions that directly drive these calculations are Working days and hours, Standard rates, and Project rates:
* A. Working days and hours: This assumption defines the available time for project execution (e.g., days per week, hours per day), directly impacting labor costs and revenue projections based on resource utilization.
* C. Standard rates: These are predefined rates (e.g., hourly or daily rates for labor or equipment) applied across projects unless overridden, driving cost and revenue calculations consistently.
* E. Project rates: These are project-specific rates that override standard rates when defined, allowing for tailored revenue and expense calculations based on unique project requirements.
* B. Plan start year: This is incorrect because, while it sets the timeline for planning, it does not directly drive revenue or expense calculations-it's a temporal parameter, not an assumption affecting financial data.
* D. Program mappings: This is incorrect because program mappings relate to integrating data across programs, not driving revenue or expense calculations within Projects.
* F. Discount rates: This is incorrect because discount rates are used for net present value (NPV) or financial analysis, not as a direct driver of revenue and expense assumptions in Projects.
The Oracle Projects module documentation highlights that Working days and hours, Standard rates, and Project rates are foundational assumptions that calculate costs (e.g., labor expenses) and revenues (e.g., billable amounts), making them the correct choices.
References:
* Oracle Planning 2024 Implementation Study Guide: "Configuring Projects Assumptions" (docs.oracle.
com, Published 2024-10-10).
* Oracle EPM Cloud Documentation: "Revenue and Expense Planning in Projects" (docs.oracle.com, Published 2023-11-25, updated for 2024).

NEW QUESTION # 51
Which task must be completed before EPM administrators import a Machine Learning model into Planning?

A. EPM Administrators create data maps and Groovy rules to move and process data.
B. EPM Administrators create a data model and push data to it to generate a PMML file.
C. Data Scientists create Groovy rules designed to evaluate historical data and identify patterns.
D. Data Scientists build and train the ML model in a data science tool and save it as a PMML file.

Answer: D

Explanation:
Before an EPM (Enterprise Performance Management) administrator can import a Machine Learning (ML) model into Oracle Planning, a prerequisite task must be completed by data scientists. According to Oracle's
"Bring Your Own ML" feature in the Planning application, the process begins with data scientists gathering historical data related to a business problem, training an ML algorithm, and generating a Predictive Model Markup Language (PMML) file using a third-party data science tool or Oracle Data Science Cloud. This PMML file represents a fully trained ML model that can then be imported into the Planning application by an EPM administrator.
Option A is correct because it aligns with this prerequisite step: the ML model must be pretrained and saved as a PMML file before the import process can begin. Option B is incorrect because Groovy rules are not created by data scientists to evaluate historical data; instead, these rules are automatically generated by the Planning application during the import process to integrate the ML model with the application. Option C is also incorrect, as EPM administrators do not generate PMML files by creating data models and pushing data- instead, they import an existing PMML file. Finally, Option D is incorrect because while EPM administrators may create data maps and Groovy rules as part of the deployment process, this occurs after the PMML file is imported, not before.
The Oracle Planning 2024 Implementation documentation emphasizes that the "Bring Your Own ML" functionality relies on importing a prebuilt PMML file, making the data scientists' role in building and training the model a mandatory first step.
References:
* Oracle Planning 2024 Implementation Study Guide: "Bring Your Own ML: About Machine Learning Model Import" (docs.oracle.com, Published 2024-09-04).
* Oracle EPM Cloud Documentation: "Importing ML Models" (docs.oracle.com, Published 2022-06-17, updated for 2024).

NEW QUESTION # 52
With Machine Learning, which type of prediction would you define to predict revenue using several input variables such as price, promotions, industry market size, and climate?

A. Forecast Prediction
B. Multivariate Prediction
C. Source Prediction
D. Dimension Prediction

Answer: B

Explanation:
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).

NEW QUESTION # 53
Which module should you enable first to track the utilization of employees in Projects?

A. Financials module before Projects module
B. Workforce module before Projects module
C. Projects module before Financials module
D. Projects module before Workforce module

Answer: B

Explanation:
To track the utilization of employees in the Projects module of Oracle Planning 2024, the Workforce module must be enabled first. Employee utilization in Projects refers to tracking how employees' time and costs (e.g., hours worked, labor expenses) are allocated to specific projects. The Workforce moduleprovides the foundational data-such as employee details, roles, salaries, and hours-required to calculate utilization metrics. Once Workforce is enabled and configured with employee data, the Projects module can leverage this data via integration to track utilization against project tasks and budgets.
* A. Projects module before Financials module: Incorrect. Enabling Projects before Financials does not address employee utilization tracking, as Financials focuses on revenue and expense planning, not employee-specific data.
* B. Financials module before Projects module: Incorrect. Financials provides financial planning capabilities but does not manage employee data or utilization, which is a Workforce function.
* C. Workforce module before Projects module: Correct. Workforce must be enabled first to define employee data, which Projects then uses to track utilization through integration (e.g., via data maps or direct links).
* D. Projects module before Workforce module: Incorrect. Enabling Projects first without Workforce would limit utilization tracking, as Projects relies on Workforce for employee-related data.
The Oracle documentation specifies that Workforce is a prerequisite for detailed employee utilization tracking in Projects, making C the correct sequence.
References:
* Oracle Planning 2024 Implementation Study Guide: "Integrating Workforce with Projects" (docs.oracle.
com, Published 2024-09-20).
* Oracle EPM Cloud Documentation: "Tracking Utilization in Projects" (docs.oracle.com, Published
2023-12-15, updated for 2024).

NEW QUESTION # 54
Which item CANNOT be pushed between cubes using data maps?

A. Attachments
B. Supporting detail
C. Data change history
D. Comments

Answer: C

Explanation:
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).

NEW QUESTION # 55
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