1Z0-1080-26 Detailed Study Dumps | Exam Cram 1Z0-1080-26 Pdf

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Oracle 1Z0-1080-26 Exam Syllabus Topics:

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

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                                          Oracle Planning + AI 2026 Implementation Professional Sample Questions (Q94-Q99):

                                          NEW QUESTION # 94
                                          Which module do you enable and configure if you want to develop plans and forecasts with driver-based or based income statement, balance sheet, and cash flow planning, or revenue and expenses?

                                          Answer: C


                                          NEW QUESTION # 95
                                          With Machine Learning, which type of prediction would you define to predict using the same dimension, measure, and slice of data?

                                          Answer: B


                                          NEW QUESTION # 96
                                          Which three features would you need to enable in order to perform indirect cash flow statement planning?

                                          Answer: B,D,E


                                          NEW QUESTION # 97
                                          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: 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 # 98
                                          Which three application types can you create and edit Groovy Rules?

                                          Answer: A,B,E


                                          NEW QUESTION # 99
                                          ......

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