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| Section | Objectives |
|---|---|
| Workflow and Approvals | - Planning workflow management
|
| Business Rules and Calculations | - Calculation framework
|
| AI and Intelligent Performance Management (IPM) | - AI-driven planning capabilities
|
| Dimensions and Security Management | - Security model
|
| Forms, Dashboards, and Navigation | - Planning UI configuration
|
| Module-Based Planning Applications | - Planning modules
|
| Reporting and Analytics | - Reporting tools
|
| Metadata and Data Integration | - Data and metadata loading
|
| Planning Application Overview & Architecture | - Oracle EPM Planning Cloud architecture
|
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質問 # 85
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?
正解：D
解説：
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.
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).
質問 # 86
With Machine Learning, which type of prediction would you define to predict using the same dimension, measure, and slice of data?
正解：A
質問 # 87
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?
正解：A、C
解説：
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).
質問 # 88
Which step does NOT need to be completed to manage the configuration of Key Performance Indicators (KPIs) in Planning Financials?
正解：D
質問 # 89
Which statement is true about the Currency dimension for Modules and Custom application types?
正解：A
質問 # 90
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