Using SAS High-Performance Forecasting Software

Duration: 3.0 days

This course teaches you how to make accurate forecasts quickly and automatically using the SAS Forecast Server procedures, giving you the power to confidently plan your business operations.

Learn how to

• process time series data
• automate the large-scale forecasting process
• add custom models and selection lists to a model repository
• create event variables to use as inputs to forecast models
• produce, assess, and modify forecasts.

Who should attend: Experienced forecasters and business analysts who can create scripts in a programming language to enhance the forecasting process

Prerequisites

Before attending this course, you should

• 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 and column totals and averages, and producing charts and plots
• have taken SAS Programming 1: Essentials or have equivalent experience.

Ideally students should have a bachelor's degree or equivalent experience in business, computer science, or a subject matter field that includes quantitative analysis. Forecasting experience is not required.

Course Contents

Introduction to Time Series Forecasting

• motivation: the large-scale forecasting problem
• time series characteristics
• time series components

Exploring and Processing Time-Stamped Data

• identifying systematic variation in the data
• accumulation: transforming transactional data into time series data
• aggregation: building the data hierarchy
• two feasible data layouts for SAS Forecast Server
• a SAS toolbox for exploring time series data

The Design of SAS High-Performance Software

• the design of SAS High-Performance Forecasting software
• functionality overview: system inputs and automatic model selection

Forecast Models

• the exponential smoothing family of models
• the ARIMA family of models
• other families of models supported: IDM, UCM
• using models in SAS Forecast Server

Diagnosing and Selecting Models Automatically

• the HPFDIAGNOSE procedure: automatic model specification
• model selection lists and automatic model selection

Managing Models and Creating Custom Models Specifications

• creating custom models: the HPFxxxSPEC procedures
• creating and managing model selection lists: the HPFSELECT procedure

Using the Events Functionality

• creating events: the HPFEVENTS procedure

Producing, Assessing, and Modifying Forecasts

• preparing to generate forecasts: accumulation and aggregation of data
• preparing to generate foreccasts: creating custom models, diagnosing models, and building a model selection list
• generating forecasts: automatic model selection and forecast outputs
• generating reconciliation effects with the HPFRECONCILE procedure and assessing forecast accuracy
• rolling the system forward in time: accommodating new data
• assessing changes in forecast accuracy and modifying forecasts

A Useful Application of the INTNX Function

• using the INTNX function to extend ID values

Software Addressed

This course addresses the following software product(s): SAS Forecast Server, SAS/ETS, SAS/STAT.

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