SAP C_SAC_2415 Practice Test - Questions Answers, Page 3

In SAP Analytics Cloud, a Time Series Forecast predictive scenario can write back to a planning model. Time Series Forecasting leverages historical data to predict future values over a specified time horizon, using statistical or machine learning methods. This feature is particularly useful in planning and forecasting processes, where future values are predicted based on past trends and seasonality. The ability to write these forecasts back into a planning model allows for the integration of predictive insights into the planning process, enhancing decision-making and strategic planning.

SAP Analytics Cloud Help Documentation: Predictive Scenarios and Planning

SAP Analytics Cloud User Guide: Time Series Forecasting in Planning Models

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.

SAP Analytics Cloud Help Documentation: Private Versions and Publishing

SAP Analytics Cloud User Guide: Working with Private Versions in Stories

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.

SAP Analytics Cloud Help Documentation: Version Management in Planning

SAP Analytics Cloud User Guide: Creating New Versions for Planning

In SAP Analytics Cloud, a data model must contain at least 'Dimensions' and 'Measures' to be functional. Dimensions are the qualitative aspects of the data (e.g., time, geography, product categories) that provide the context for analysis. Measures, on the other hand, are the quantitative data points (e.g., sales, costs, quantities) that are analyzed within the context provided by dimensions. Both are fundamental components of a data model, enabling structured data analysis and reporting.

SAP Analytics Cloud Help Documentation: Building Data Models

SAP Analytics Cloud User Guide: Understanding Dimensions and Measures in Models