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SAS(R) High-Performance Markdown Optimization Analytics and Modeling

Course Details
Code: SMIMAM43
Tuition (USD): $1,625.00 • Classroom (2.5 days)

This course is for those responsible for demand modeling within a retail organization in which SAS High-Performance Markdown Optimization has been implemented.

Skills Gained

  • use of the SAS Foundation (Display Manager) software to submit simple queries against the Merchandise Intelligence datamart
  • use of the SAS High-Performance Merchandise Solutions Configuration Workbench to configure demand models for estimation and forecasting
  • analysis of modeling input data to evaluate its adequacy for modeling
  • scenario-based analysis of model parameter estimates and forecast accuracy
  • an overview of the weekly processes related to ongoing data loads, the refreshing of demand model input data, and the recalibration and monitoring of demand models.

Who Can Benefit

  • Those responsible for demand modeling within a retail organization, including client staff who will be performing or require deep understanding of Markdown Optimization modeling, and SAS Consultants who will be performing or shadowing Markdown Optimization modeling for clients


  • Before attending this course, you should have
  • basic skills using Microsoft Windows and Windows-based software
  • solid understanding of time series forecasting in a business context
  • understanding of retail hierarchical data
  • basic understanding of SAS programming, with exposure to the use of SAS macros.

Course Details

Environment Overview

  • SAS Merchandise Intelligence Architecture
  • Production and Supporting Environments
  • training environment for this course

Demand Modeling Overview

  • how demand modeling works
  • estimation tasks
  • retail data hierarchies
  • custom attributes

Getting Started in the Configuration Workbench

  • setting preferences and data sources
  • configuring global settings
  • about data load editors

Pre-Markdown Analytics and Modeling

  • review of analytics and modeling environment
  • pre-markdown analytics and modeling tasks
  • basic analysis of data mart
  • model group configuration
  • model group analyses
  • model group scheduling and templates

Additional Topics

  • ongoing holdout forecast analysis
  • monitoring forecasts
  • adjusting forecasts
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