A00-255 exam dumps

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  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • No. of Questions: 87 Questions and Answers
  • Updated: Oct 05, 2026

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The SAS Institute A00-255 exam is intended for professionals who want to gain knowledge and experience in predictive modeling using SAS Enterprise Miner 14. A00-255 exam covers topics like data exploration, variable selection, model building, model assessment, and deployment. A00-255 exam is intended for professionals who work with large datasets and want to use predictive modeling to make data-driven decisions.

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SASInstitute A00-255 exam consists of multiple-choice questions that cover various topics related to predictive modeling, including data preparation, variable selection, model assessment, and deployment. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification program is suitable for data analysts, statisticians, and data scientists who want to enhance their skills in data mining and predictive modeling.

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SASInstitute A00-255 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Building Predictive Models35-40%- Model Development
  • 1. Describe predictive modeling concepts and terminology
  • 2. Build neural network models
  • 3. Build regression models
  • 4. Build decision tree models
Topic 2: Data Sources20-25%- Create and Explore Data Sources
  • 1. Explore and assess data sources
  • 2. Create data sources from SAS tables in Enterprise Miner
- Prepare Source Data
  • 1. Modify source data
  • 2. Prepare data for predictive modeling
Topic 3: Predictive Model Assessment and Implementation25-30%- Model Deployment
  • 1. Score data sets within Enterprise Miner
- Model Evaluation
  • 1. Use decision processing for oversampling adjustment
  • 2. Assess model performance using profit and loss information
  • 3. Compare models using Model Comparison node
  • 4. Select appropriate fit statistics
Topic 4: Pattern Analysis10-15%- Segmentation and Association Analysis
  • 1. Identify clusters using Cluster and Segment Profile nodes
  • 2. Perform association analysis
  • 3. Perform sequence analysis and market basket analysis

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