SAS Forecasting is a software tool that enables users to predict future trends and outcomes using historical data. It employs advanced statistical methods and analytics to generate accurate forecasts, helping organizations make informed decisions by anticipating demand, sales, inventory needs, and other critical business metrics.
About 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.
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How to hire a SAS Forecasting expert
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.
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