In SAP Analytics Cloud, what is the purpose of regression analysis in forecasting?

The purpose of regression analysis in forecasting within SAP Analytics Cloud is to model relationships between variables. This statistical method enables users to understand how different factors impact outcomes, allowing for the creation of predictive models based on historical data. By examining the relationships between the dependent variable (the variable being predicted) and one or more independent variables (the predictors), regression analysis helps identify trends and influences that can be expected to continue into the future.

This is particularly valuable in forecasting scenarios where businesses want to predict future sales, revenues, or other key metrics based on known influencing factors, such as advertising spend, seasonality, or economic indicators. Utilizing regression analysis empowers decision-makers with data-driven insights that can enhance strategic planning and operational efficiency.

In contrast, the other options provided do not align with the primary function of regression analysis in the context of forecasting. Data cleansing focuses on preparing data for analysis by removing inconsistencies or inaccuracies, currency conversion deals with financial data processing, and anomaly detection is focused on identifying outliers or unusual patterns in the data. While these processes may be important in data handling and analysis, they do not specifically relate to the core function of regression analysis in forecasting.