This course prepares you to generate large volumes of forecasts automatically using the SAS Forecast Studio interactive interface. This course includes practice data and exercises.
This course supports both the desktop and client/server versions. Additional topics for students that license the client/server version of SAS Forecast Studio include producing reports using sample stored processes and a demonstration of SAS Time Series Studio.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual Lab time to practice.
Learn How To
automatically create and fit custom forecast models to large-scale time series data sets identify series that do not have acceptable forecast accuracy refine forecast models to improve forecast accuracy reconcile hierarchical forecasts generate forecast data sets for deployment accommodate data updates in large-scale time series data sets.Who Should Attend
Forecasters and analysts in any industry, including retail, financial services, manufacturing, and pharmaceuticals
Prerequisites
Before attending this course, you should;
be familiar with business forecasting problems have experience with a Windows computing environment have experience using a product such as Microsoft Excel to enter or transfer data and to perform elementary analyses such as computing row totals, column totals, and averages, and producing charts and plots. ;You do not need formal training in forecasting or statistics to benefit from this course. Programming experience is also not required.SAS Products Covered
SAS/STAT;SAS Forecast Server
Course Outline
Introduction to SAS Forecast StudioForecasting Using the Default Functionality in SAS Forecast Studio
creating a SAS Forecast Studio project accuracy statistics and forecast model selection families of models supported and functionality issues scenario analysisHierarchical Forecastinghierarchical forecasting statistical forecast reconciliation accumulation and aggregation options reconciliation effects manual overrides to reconciled forecastsModel Refinement One Series at a Timecustom models: generated and pre-specified event variablesGenerating Best Forecasts in Hierarchically Arranged Datahonest assessment outlier variables and other model inputs creating and using event variables based on calendar effects generated data sets accommodating data updatesProject Monitoring and Selected Topicstools for project maintenance and management alternative assessment approaches combined model forecastsProducing Reportsusing stored processes to produce reports discussing sample stored processes that are provided with the client/server version of SAS Forecast ServerSAS Time Series Studiousing SAS Time Series Studio to aid in the data creation process
