SAS Forecasting

SAS Forecasting was developed by SAS Institute, which was founded by Anthony J. Barr, James Goodnight, John Sall, and Jane Helwig in 1976. It emerged as part of SAS's suite of analytics tools aimed at providing businesses with the ability to predict future trends using historical data. The tool evolved over the years to incorporate advanced statistical methods and machine learning techniques to improve the accuracy and reliability of forecasts for various business applications.

Strengths of SAS Forecasting include its robust analytical capabilities, user-friendly interface, and ability to handle large datasets with complex statistical models. Weaknesses may involve high costs and a steep learning curve for new users. Competitors include IBM SPSS, Oracle Crystal Ball, and Microsoft Azure Machine Learning.

A SAS Forecasting expert must have strong skills in statistical analysis, proficiency in SAS programming, and experience with time series analysis. Knowledge of data manipulation and cleaning techniques is essential, along with the ability to interpret and communicate complex forecasting results. Familiarity with machine learning algorithms used within the SAS environment is also beneficial.