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Oracle 1Z0-1080-26 Exam Syllabus Topics:

Section	Objectives
Topic 1: Planning Application Configuration	- Application design 1. Planning models setup 2. Metadata structure and dimensions - Business rules and calculations 1. Rule creation and validation 2. Calculation logic for planning scenarios
Topic 2: Data Integration and Management	- Data loading methods 1. Data imports and exports 2. Source system integration - Data validation and transformation 1. Mapping and transformation rules 2. Data reconciliation techniques
Topic 3: Oracle Enterprise Performance Management (EPM) Cloud Overview	- Security and user management 1. Roles and access control 2. Application security configuration - EPM architecture and components 1. Data flow and integration concepts 2. Planning Cloud services overview
Topic 4: Reporting and Analysis	- Financial reporting 1. Report creation and customization 2. Dashboard configuration - Analytics 1. Variance analysis 2. Performance monitoring
Topic 5: AI and Predictive Planning Features	- Predictive forecasting 1. Forecast generation and adjustment 2. Trend-based planning models - AI-assisted planning insights 1. Driver-based planning concepts 2. Anomaly detection and recommendations

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Oracle Planning + AI 2026 Implementation Professional Sample Questions (Q36-Q41):

NEW QUESTION # 36
Which three options can you enable for Manage Existing Assets in Capital?

A. Leased Assets
B. Improvements/Impairments
C. Named Assets
D. Transfers
E. Retirements

Answer: B,D,E

NEW QUESTION # 37
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?

A. 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.
B. For future data, create a new insight by leveraging templates that include insight definitions.
C. For historical data, there should be at least twice the amount of historical data as the number of prediction periods.
D. For future data, first run predictions in a test environment to ensure there is no impact on production data.

Answer: C,D

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 # 38
Which item CANNOT be pushed between cubes using data maps?

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

Answer: B

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.
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 # 39
Which three sources of data can you use in Dashboards 2.0?

A. Ad hoc grids
B. Forms
C. Spreadsheets
D. Cubes
E. Reports

Answer: A,B

NEW QUESTION # 40
Which client requirement aligns with using a custom BSO plan type along with or in place of the Workforce module?

A. Because of sparse dimensionality, aggregation times are slow in the Workforce module.
B. The client would like to plan salary by Position.
C. The client requires more than three custom dimensions.
D. The Operations department requires a more granular level of detail than the Sales department in the Entity dimension.
E. The client has 10 dimensions in the application and needs to report at each intersection.

Answer: A

NEW QUESTION # 41
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