This page was exported from Valid Premium Exam [ http://premium.validexam.com ] Export date:Thu Apr 3 22:13:21 2025 / +0000 GMT ___________________________________________________ Title: [Mar 30, 2025] Get Unlimited Access to C_SAC_2415 Certification Exam Cert Guide [Q12-Q26] --------------------------------------------------- [Mar 30, 2025] Get Unlimited Access to C_SAC_2415 Certification Exam Cert Guide Reliable Study Materials for C_SAC_2415 Exam Success For Sure SAP C_SAC_2415 Exam Syllabus Topics: TopicDetailsTopic 1Data Modeling, Analysis, and Integration: This section evaluates the expertise of professionals in data modeling and analytics. It emphasizes the creation and configuration of models within SAP Analytics Cloud (SAC), detailing the role and functionalities of the Data Analyzer, and integrating SAC with external applications.Topic 2Planning: This section measures the proficiency of planning and financial analysts in utilizing SAP Analytics Cloud's enterprise planning features. It covers working with planning models and stories, configuring data actions, managing versions, and conducting forecasting and simulations.Topic 3Story Design: This section assesses the skills of data analysts and report designers. It includes the design and presentation of stories within SAC, with a focus on configuring story elements such as pages, tables, charts, and widgets.Topic 4Performance, Troubleshooting, and Security Management: This section is designed for system administrators and security managers. It involves identifying performance issues, understanding their causes and solutions, and explaining the security model of SAP Analytics Cloud.Topic 5Connections and Data Preparation: This section targets data integration specialists and preparers. It involves identifying the various methods SAC employs to access data and understanding the appropriate use cases for each.   Q12. What can you do with a multi action? Note: There are 2 correct answers to this question.  Run allocation data actions  Import transaction data  Approve data  Run allocation processes Q13. In a data model, what can you use to further describe a dimension?  Data action  Measure  Property  Variable In a data model within SAP Analytics Cloud, Properties are used to further describe dimensions. Properties provide additional context or metadata for dimension members, such as descriptions, classifications, or other attributes that help to better understand and analyze the data within the dimension. This makes properties essential for detailed data analysis and reporting.Reference:SAP Analytics Cloud Help Documentation: Dimension PropertiesSAP Analytics Cloud User Guide: Enhancing Dimensions with PropertiesQ14. You need to delete characters from a column in a dataset. What can you use? Note: There are 2 correct answers to this question.  Custom expression editor  Formula bar  Calculation editor  Transform bar Q15. When scrolling down in a long table, how can you retain column headers? Note: There are 2 correct answers to this question.  Enable Keeping member names visible  Enable Auto-Size And Page Table Vertically  Freeze Up to row  Freeze Up to column Q16. You are using a live connection for a model. Where is the data stored?  Public dataset  SAP Analytics Cloud model  Source system  Embedded data set Connections and data preparationWhen using a live connection in SAP Analytics Cloud, the data remains stored in the source system. This means that no data is imported or replicated into SAP Analytics Cloud; instead, it is accessed and analyzed in real-time directly from the source system. This approach ensures that the most current data is always used for analysis and that data governance and security policies of the source system remain in control.Reference:Live Data Connections to SAP S/4HANA | SAP Help Portal1SAP Analytics Cloud Connection Guide2SAP Analytics Cloud Data Connections – InsightCubesIn the context of SAP Analytics Cloud, when using a live connection to connect to a data source, the data remains stored in the source system. This setup means that SAP Analytics Cloud directly queries the data in its original location, without importing or copying it into the SAP Analytics Cloud environment. This approach is advantageous for several reasons, including maintaining a single source of truth, reducing data redundancy, and ensuring data is always up-to-date without the need for synchronization processes. Live connections are particularly useful for real-time or near-real-time data analysis and reporting, providing insights based on the most current data available without the overhead of data replication.SAP Analytics Cloud documentation and user guides typically emphasize the benefits and use cases of live connections, highlighting how they maintain data in the source system to ensure real-time data access and analysis.SAP training materials for Data Analysts using SAP Analytics Cloud, including study guides and official certification resources, explain the technical and practical aspects of live connections, including where data is stored and how it is accessed.Best practice guides for SAP Analytics Cloud, often available through the SAP Community or SAP Knowledge Base, provide insights and recommendations on setting up and using live connections, reinforcing the concept that data stays in the source system.Q17. Which of the following data sources can you use in SAP Analytics Cloud data analyzer? Note: There are 3 correct answers to this question.  SAP Analytics Cloud public dataset  SAP HANA view  SAP Datasphere model  SAP Analytics Cloud analytic model  SAP BusinessObjects Universe Q18. Where can you create a blank planning version?  In a data cell  In version management  In the version dimension  In the planning model A blank planning version in SAP Analytics Cloud can be created within the Version Management feature. This area of the platform allows users to manage different versions of their data, such as budgets, forecasts, and what-if scenarios. Creating a blank version provides a clean slate for planning activities, without pre-existing data, enabling users to start fresh with their assumptions and inputs.Reference:SAP Analytics Cloud Help Documentation: Version Management in PlanningSAP Analytics Cloud User Guide: Creating New Versions for PlanningQ19. The SAP Analytics Cloud (SAC) modeler has removed the first three characters from an SAP Analytics Cloud public dimension imported from a source system. What is impacted by this change?  Public datasets  Source system  Stories  Embedded data sets When the SAP Analytics Cloud (SAC) modeler removes the first three characters from a public dimension imported from a source system, this change impacts Stories that use this dimension. Specifically, any visualizations, calculations, or filters within those stories that rely on the original dimension values may need to be adjusted to account for the change. This modification does not affect the source system or public datasets directly, but it can impact how the data appears and behaves in stories that use the modified dimension.Reference:SAP Analytics Cloud Help Documentation: Modifying DimensionsSAP Analytics Cloud User Guide: Impact of Dimension Changes on StoriesQ20. Which dimension type can you use like a measure?  Account  Date  Organization  Entity In SAP Analytics Cloud, the Account dimension can be used similarly to a measure. This dimension is specifically designed for financial data and can hold various types of financial metrics, such as revenues, expenses, assets, and liabilities. It allows for the application of financial calculations and aggregations, which is why it can function similarly to measures in the context of financial reporting and analysis.Reference:SAP Analytics Cloud Help Documentation: Understanding Dimensions and Measures SAP Analytics Cloud User Guide: Working with Account DimensionsQ21. You input new data for a private version in a story. What must you do to ensure the new data is added to the model?  Save  Send  Publish  Nothing When inputting new data for a private version in a story in SAP Analytics Cloud, it is necessary to “Publish” the data to ensure it is added to the model. Publishing the private version commits the changes to the underlying model, making the new data visible and accessible to other users according to their permissions. This step is crucial for ensuring that the updated data is incorporated into the shared model for further analysis and decision-making.Reference:SAP Analytics Cloud Help Documentation: Private Versions and Publishing SAP Analytics Cloud User Guide: Working with Private Versions in StoriesQ22. Which features are available in the Optimized Design Experience? Note: There are 3 correct answers to this question.  Undo button  Grid pages  Linked widgets diagram  Composites  Explorer Q23. Which automatically created dimension type can you delete from an analytic data model?  Version  Date  Organization  Generic In an analytic data model within SAP Analytics Cloud, the automatically created dimension type that you can delete is the Generic dimension. This type of dimension is typically used for custom or ad-hoc categorizations and, unlike system-generated dimensions like Date or Version, can be modified or removed as per the specific needs of your data model and analysis requirements.Reference:SAP Analytics Cloud Help Documentation: Data Model DimensionsSAP Analytics Cloud User Guide: Managing Dimensions in Analytic ModelsQ24. You import data into a dataset. One of the columns imported is Year, and SAP Analytics Cloud interprets it as a measure. How can you ensure that it is treated as a calendar year?  Change the Year measure to a dimension in the dataset.  Includes the Year measure in a level-based time hierarchy in the dataset.  Insert a character into the Year measure using the transform bar.  Add the month as a suffix to the Year measure. If SAP Analytics Cloud interprets a ‘Year’ column as a measure instead of a dimension, it should be changed to a dimension to ensure it is treated as a calendar year. This adjustment can be made within the model or dataset settings, where the column’s role can be switched from a measure (quantitative value) to a dimension (qualitative value). Treating ‘Year’ as a dimension allows it to be used appropriately in time-based analyses, such as trends over time, without being aggregated like a numerical measure.Q25. You are creating a script for an advanced data action. Which character designates a virtual variable member?  %  /  *  # Q26. Your users need to analyze data in a story. What kinds of data models can you create? Note: There are 2 correct answers to this question.  Standalone  Embedded  Planning  Analytic  Loading … New SAP C_SAC_2415 Dumps & Questions: https://www.validexam.com/C_SAC_2415-latest-dumps.html --------------------------------------------------- Images: https://premium.validexam.com/wp-content/plugins/watu/loading.gif https://premium.validexam.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2025-03-30 14:10:53 Post date GMT: 2025-03-30 14:10:53 Post modified date: 2025-03-30 14:10:53 Post modified date GMT: 2025-03-30 14:10:53