SAS Text Analytics, Time Series, Experimentation and Optimization

Exam Content Guide

Below we provide a list of the objectives that will be tested on the exam.
For more specific details about each objective download the complete exam content guide.


Text Analytics - 30%

  • Create data sources for text mining
  • Import data into SAS Text Analytics
  • Use text mining to support forensic linguistics using stylometry techniques
  • Retrieve information for Analysis
  • Parse and quantify Text
  • Perform predictive modeling on text data
  • Use the High-Performance (HP) Text Miner Node

Time Series - 30%

  • Identify and define time series characteristics, components and the families of time series models
  • Diagnose, fit, and interpret ARIMAX Models
  • Diagnose, fit, and interpret Exponential Smoothing Models
  • Diagnose, fit, and interpret Unobserved Components Models

Experimentation & Incremental Response Models - 20%

  • Explain the role of experiments in answering business questions
  • Relate experimental design concepts and terminology to business concepts and terminology
  • Explain how incremental response models can identify cases that are most responsive to an action
  • Use the Incremental Response node in SAS Enterprise Miner

Optimization - 20%

  • Optimize linear programs
  • Optimize nonlinear programs

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