SAP C_SAC_2415 - SAP Certified Associate - Data Analyst - SAP Analytics Cloud

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.

References:

SAP Analytics Cloud Help Documentation: Predictive Scenarios and Planning

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

When you have a dimension with members for product groups and associated products and want to plan by product group without disaggregating into the individual products, using two hierarchies is the best approach. One hierarchy can represent the product groups at a higher level, allowing for planning and analysis at the group level. The second hierarchy can include both the product groups and their associated individual products for more detailed analysis when needed. This approach provides flexibility in planning and analyzing data at different levels of detail without the necessity of disaggregating data at the product group level.

References:

SAP Analytics Cloud Help Documentation: Hierarchies in Planning

SAP Analytics Cloud User Guide: Managing Hierarchies for Planning

To combine two dimensions, Firstname and Lastname, into a single dimension displaying as Lastname, Firstname in a live data model, you should create a calculated dimension in the data model. This calculated dimension will concatenate the two fields into one, according to the specified format. This approach allows for the creation of a new dimension that can be used across various reports and analyses within the model, maintaining the integrity of the original dimensions.

References:

SAP Analytics Cloud Help Documentation: Creating Calculated Dimensions

SAP Analytics Cloud User Guide: Data Modeling Best Practices

To transform data in a dataset using if/then/else logic in SAP Analytics Cloud, you must use the Custom expression editor. This tool allows you to write complex logical conditions and perform conditional data transformations. The steps involved are:

Open the dataset you want to transform.

Navigate to the "Custom expression editor".

Write your if/then/else logic using the syntax supported by SAP Analytics Cloud. For example:

IF([Sales] > 1000, "High", "Low")

Apply the expression to the relevant column.

Validate and save your changes.

This approach allows for flexibility and precision in transforming your data based on specific conditions.

References:=

SAP Help Portal: SAP Analytics Cloud

Official SAP Analytics Cloud Documentation

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 storiesthat 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.

References:

SAP Analytics Cloud Help Documentation: Modifying Dimensions

SAP Analytics Cloud User Guide: Impact of Dimension Changes on Stories