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 Forecasting
hierarchical forecasting
statistical forecast reconciliation
accumulation and aggregation options
reconciliation effects
manual overrides to reconciled forecastsModel Refinement One Series at a Time
custom models: generated and pre-specified
event variablesGenerating Best Forecasts in Hierarchically Arranged Data
honest 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 Topics
tools for project maintenance and management
alternative assessment approaches
combined model forecastsProducing Reports
using stored processes to produce reports
discussing sample stored processes that are provided with the client/server version of SAS Forecast ServerSAS Time Series Studio
using SAS Time Series Studio to aid in the data creation process
The hands-on lab is preconfigured to support this course and will not support hands-on practice for all your enrolled courses.
Hands-On Lab Reservation System
When you are planning your study time, keep in mind that the virtual lab takes 60-75 minutes to start
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