This course teaches you how to create and manage a complete forecasting system 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 forecasting of the majority of your series in a large-scale forecasting process handle exceptions by adding custom models and selection lists to a model repository create and manage event variables and event variable data sets to use as inputs to forecast models implement best practices in model selection, data hierarchy construction, and statistical forecast reconciliation processes.Who Should Attend
Experienced data scientists and analytic leads who want to learn to develop scripts in the SAS Forecast Server programming language to build, maintain, and optimize the performance of their forecasting system
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 Forecasting Using SAS(R) Forecast Server Software or have equivalent experience with time series data and modeling have taken SAS(R) Programming I: 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 helpful but not required.SAS Products Covered
SAS/STAT;SAS Forecast Server;SAS/ETS
Course Outline
Introduction
motivation: the large-scale forecasting problem layout of the courseExploring and Processing Timestamped Dataaccumulation: transforming transactional data into time series data handling missing and zero-valued intervals aggregation: building the data hierarchy two feasible data layouts for SAS Forecast Server using the TIMEDATA procedure identifying systematic variation in the data a SAS toolbox for exploring time series dataThe Design of SAS Forecast Server-Based Forecasting Softwarethe design of SAS Forecast Server-based forecasting software functionality overview: system inputs and automatic model selectionDiagnosing and Selecting Models AutomaticallyHPFDIAGNOSE procedure: automatic model specification model selection lists and automatic model selectionCreating Custom Models and Managing Model Listscreating custom models: HPFxxxSPEC procedures creating and managing model selection lists: HPFSELECT procedureUsing the Events Functionalitycreating and managing event variables: HPFEVENTS procedure using the HPFEVENTS procedure: extensions and further detailsReconciling Statistical Forecastsbasic forecast reconciliation using the HPFRECONCILE procedure disaggregation methods in forecast reconciliationProducing, Assessing, and Modifying Forecastshonest assessment preparing to generate forecasts: accumulation and aggregation of the data preparing to generate forecasts: creating custom models, diagnosing models, and building a model selection list generating forecasts: automatic model selection and forecast outputs assessing system accuracy and generating reconciled forecastsRolling the Forecasting System Forward in Timeforecasting by exception assessing model degradation handling data updates and structural changes
