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SASInstitute Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya : A00-274 Exam

A00-274 Exam Questions
  • Exam Code: A00-274
  • Exam Name: Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya
  • Updated: Aug 23, 2026
  • Q & A: 0 Questions and Answers

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SASInstitute A00-274 certification exam covers a wide range of topics, including data preparation, model building, data visualization, and model deployment. You will be tested on your ability to use SAS Viya to build interactive models, create visualizations, and deploy models in production environments. You will also be tested on your knowledge of advanced statistical modeling techniques, such as decision trees, regression analysis, and clustering.

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SASInstitute A00-274 certification exam covers various topics, including exploratory data analysis, data preparation, regression analysis, classification analysis, clustering analysis, and predictive modeling. A00-274 exam also tests the candidate's knowledge of SAS Viya architecture and the SAS Visual Statistics interface.

SASInstitute A00-274 certification is designed for data analysts, data scientists, and statisticians who want to enhance their skills in SAS Visual Statistics 8.4. SAS Visual Statistics 8.4 is an interactive tool that can be used to create and modify predictive models. The SASInstitute A00-274 certification exam tests the candidate's proficiency in using SAS Visual Statistics 8.4 to build interactive models on the SAS Viya platform.

SASInstitute A00-274 Exam Syllabus Topics:

SectionWeightObjectives
Building and Assessing Segmentation Models28%- Supervised segmentation using decision trees
- Assess and interpret decision tree performance
- Unsupervised segmentation using cluster analysis
- Interpret and analyze cluster results
SAS Visual Statistics Cross-Functional Tasks22%- Prepare data using SAS Visual Analytics
- Use interactive group-by functionality
- Perform model validation
- Filter data for modeling
Building and Assessing Regression-Type Models41%- Explain linear model concepts and assumptions
- Perform nonparametric logistic regression modeling
- Build generalized additive models
- Evaluate linear regression model results
- Interpret and validate regression model outputs
- Perform linear regression modeling
Model Comparison and Scoring9%- Interpret scoring results
- Apply models to score new data
- Compare multiple models using appropriate metrics

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