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