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Oracle 1z0-1080-24 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	Manage Approvals:This section of the exam measures the skills of approval process managers and covers setting up approval workflows in Planning. It explains how to configure approval processes to streamline decision-making within organizations.
Topic 3	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 4	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 5	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 6	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 7	Manage Forms, Dashboards, and Navigation Flows: This section of the exam measures the skills of dashboard designers and covers designing forms, dashboards, and validation rules. It also includes creating and managing navigation flows to streamline user experience within Planning applications.
Topic 8	Manage Metadata and Data: This section of the exam measures the skills of data integration specialists and covers metadata and data management in Planning. It includes identifying metadata and data load options, importing and exporting metadata and data, setting up and running data maps, creating data integrations, and mapping data across applications.
Topic 9	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 (Q18-Q23):

NEW QUESTION # 18
What two levels of workforce detail granularity would you need to perform Merit-Based Planning?

A. Employee and Job
B. Merit
C. Job
D. Employee

Answer: A,D

Explanation:
In Oracle Planning 2024's Workforce module, Merit-Based Planning involves planning salary increases or adjustments based on employee performance (merit). To perform this, you need workforce data at a level of granularity that includes individual employee details. The two levels required are:
* A. Merit: Incorrect. "Merit" is not a granularity level; it's a planning concept or assumption applied to employee data, not a structural level of detail.
* B. Employee and Job: Correct. This level combines employee-specific data (e.g., individual identity) with job-specific data (e.g., role, grade), enabling merit-based adjustments tailored to both the person and their position.
* C. Job: Incorrect. Job-level granularity (e.g., aggregated data for a role) lacks individual employee details, which are necessary for merit-based planning.
* D. Employee: Correct. Employee-level granularity provides the individual data (e.g., current salary, performance rating) needed to calculate merit increases for specific employees.
Merit-Based Planning requires at least Employee-level detail, and often Employee and Job for more precise planning (e.g., tying merit to job roles or grades). The Oracle documentation confirms these as the key granularity levels for this functionality, making B and D the correct answers.
References:
* Oracle Planning 2024 Implementation Study Guide: "Merit-Based Planning in Workforce" (docs.oracle.
com, Published 2024-10-10).
* Oracle EPM Cloud Documentation: "Workforce Granularity Levels" (docs.oracle.com, Published 2023-
11-15, updated for 2024).

NEW QUESTION # 19
You are preparing to design a report in Cloud EPM Planning using Report Designer. Which two statements are true about data sources in reports?

A. Insert a report object into the report if you are in Modify mode.
B. Control the way a report object is printed on the page relative to other report objects.
C. Include a chart in your report without displaying the underlying data grid.
D. Insert charts in the report header to provide a quick visual summary of data.

Answer: B,C

Explanation:
When designing reports in Oracle Cloud EPM Planning using Report Designer, data sources and report objects (e.g., grids, charts) have specific capabilities. The two true statements about data sources in reports are:
* A. Insert charts in the report header to provide a quick visual summary of data: Incorrect. Report Designer does not support inserting charts directly into the report header; charts are added as objects within the report body, linked to data sources.
* B. Include a chart in your report without displaying the underlying data grid: Correct. You can create a chart object tied to a data source (e.g., a grid) and configure it to display only the chart, suppressing the grid for a cleaner visual presentation.
* C. Control the way a report object is printed on the page relative to other report objects: Correct. Report Designer allows you to adjust the layout and positioning of report objects (e.g., grids, charts) relative to each other, controlling how they appear when printed or exported.
* D. Insert a report object into the report if you are in Modify mode: Incorrect. While you modify reports in Report Designer, there's no specific "Modify mode" restriction-objects can be inserted during initial design or edits, but this is not a data source-specific feature.
The Oracle documentation verifies that B and C reflect Report Designer's flexibility with data sources and object management, making them the correct answers.
References:
* Oracle Planning 2024 Implementation Study Guide: "Designing Reports with Report Designer" (docs.
oracle.com, Published 2024-09-30).
* Oracle EPM Cloud Documentation: "Report Designer Data Sources" (docs.oracle.com, Published 2023-
12-05, updated for 2024).

NEW QUESTION # 20
You need to schedule a weekly data import job. Which two statements are true about scheduling jobs?

A. You can check the execution status of a job only if it completed.
B. You can set the daily maintenance time when scheduling cloning environment jobs.
C. You can schedule an Import Data job to run later at intervals.
D. You can set to receive notifications when the job has completed.
E. You can delete that are currently processing.

Answer: C,D

Explanation:
In Oracle Planning 2024, scheduling jobs such as a weekly data import is managed through the Jobs interface, which provides options for automation, monitoring, and notifications. Let's evaluate the provided statements to identify the two that are true:
* A. You can check the execution status of a job only if it completed: This is false. The Jobs console in Oracle EPM allows users to check the status of a job (e.g., Running, Completed, Failed) at any time, not just after completion. Real-time monitoring is a key feature.
* B. You can set the daily maintenance time when scheduling cloning environment jobs: This is false.
Daily maintenance time is a system-wide setting controlled by administrators via Application Settings, not something adjustable when scheduling specific jobs like cloning or data imports.
* C. You can set to receive notifications when the job has completed: This is true. When scheduling a job (e.g., Import Data), users can enable email notifications to be alerted upon job completion, success, or failure, enhancing job management.
* D. You can schedule an Import Data job to run later at intervals: This is true. The scheduling feature supports recurring jobs, such as weekly data imports, allowing users to define the start time and frequency (e.g., daily, weekly) for tasks like importing data from external sources.
* E. You can delete that are currently processing: This is false. Jobs that are currently processing (i.e., in a "Running" state) cannot be deleted until they complete or fail, as per Oracle's job management rules.
Thus, the two true statements are C and D, reflecting the flexibility of scheduling recurring Import Data jobs and receiving completion notifications, both of which are explicitly supported in Oracle Planning 2024.
References:
* Oracle Planning 2024 Implementation Study Guide: "Managing Jobs and Scheduling" (docs.oracle.
com, Published 2024-08-22).
* Oracle EPM Cloud Documentation: "Scheduling Jobs in Planning" (docs.oracle.com, Published 2023-
12-10, updated for 2024).
* Oracle Planning Administration Guide: "Monitoring and Notifications" (docs.oracle.com, Published
2024-10-01).

NEW QUESTION # 21
Which task must be completed before EPM administrators import a Machine Learning model into Planning?

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

Answer: B

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 # 22
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 atleast 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.
References:
* Oracle Planning 2024 Implementation Study Guide: "Configuring Insights and Auto Predict" (docs.
oracle.com, Published 2024-10-15).

NEW QUESTION # 23
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Oracle Planning 2024 Implementation Professional Sample Questions (Q18-Q23):

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