What is multi-linear regression in SAP EPM-BPC - Business Planning and Consolidation?

SAP Term: multi-linear regression

• Component: EPM-BPC

• Component Name: Business Planning and Consolidation

• Description: An algorithm type the system uses when making predictions and analyzing root causes in Insight.

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• Key Concepts: 
  Multi-linear regression is a statistical technique used in the SAP Business Planning and Consolidation (EPM-BPC) component to analyze the relationship between multiple independent variables and a single dependent variable. It is used to identify the most important factors that influence the dependent variable, and to predict its value based on the values of the independent variables. 
  
  How to use it: 
  In order to use multi-linear regression in SAP EPM-BPC, you must first define the independent and dependent variables. The independent variables are those that are believed to influence the dependent variable, while the dependent variable is the one whose value is being predicted. Once these variables have been identified, you can then use multi-linear regression to analyze their relationship and make predictions about the value of the dependent variable. 
  
  Tips & Tricks: 
  When using multi-linear regression in SAP EPM-BPC, it is important to ensure that all of the independent variables are relevant to the dependent variable. If irrelevant variables are included, this can lead to inaccurate results. Additionally, it is important to ensure that all of the data used for analysis is accurate and up-to-date. 
  
  Related Information: 
  Multi-linear regression is just one of many statistical techniques available in SAP EPM-BPC. Other techniques include linear regression, logistic regression, and time series analysis. Additionally, there are a variety of other tools available in SAP EPM-BPC that can be used for data analysis and forecasting.