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| Section | Objectives |
|---|---|
| Topic 1: Workflow and Approvals | - Planning workflow management
|
| Topic 2: Reporting and Analytics | - Reporting tools
|
| Topic 3: Metadata and Data Integration | - Data and metadata loading
|
| Topic 4: AI and Intelligent Performance Management (IPM) | - AI-driven planning capabilities
|
| Topic 5: Business Rules and Calculations | - Calculation framework
|
| Topic 6: Dimensions and Security Management | - Security model
|
| Topic 7: Forms, Dashboards, and Navigation | - Planning UI configuration
|
| Topic 8: Module-Based Planning Applications | - Planning modules
|
| Topic 9: Planning Application Overview & Architecture | - Oracle EPM Planning Cloud architecture
|
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NEW QUESTION # 118
If you are using your own chart of accounts and want to use dashboards that graphically depict total results, you must add your accounts as shared members under the appropriate parent. To which four parent members do you add your own chart of accounts as shared members, to include them in predefined dashboards?
Answer: B,D,E,F
NEW QUESTION # 119
Which task must be completed before EPM administrators import a Machine Learning model into Planning?
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.
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 # 120
You want to analyze past data and predicted data to help you find patterns and insights into data that you might not have found on your own. To accomplish this, you configure Insights with Auto Predict.
Which two are Oracle EPM guidelines for implementing Insights and Auto Predict?
Answer: A,C
Explanation:
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.
Oracle Planning 2024 Implementation Study Guide: "Configuring Insights and Auto Predict" (docs.oracle.com, Published 2024-10-15).
NEW QUESTION # 121
Which module should you enable first to track the utilization of employees in Projects?
Answer: D
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 module provides 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.
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 # 122
A company has enabled Financials and would now like to make changes to the initial configuration. Which three changes can be made?
Answer: A,C,F
NEW QUESTION # 123
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