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Instant Download SASInstitute : A00-274 Questions & Answers as PDF & Test Engine
- Exam Code: A00-274
- Exam Name: Interactive Model Building using SAS Visual Statistics 8.4 on SAS Viya
- Updated: Aug 01, 2026
- No. of Questions: 0 Questions and Answers
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SASInstitute A00-274 exam measures the candidate's ability to use SAS Viya for interactive model building, data exploration, and analysis. A00-274 exam covers a wide range of topics, including exploring data with SAS Viya, building and assessing predictive models using SAS Visual Statistics, and creating interactive reports and dashboards. A00-274 exam consists of multiple-choice questions and performance-based tasks that require the candidate to demonstrate their practical skills in SAS Viya.
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The SASInstitute A00-274 exam covers a variety of topics related to interactive model building using SAS Visual Statistics 8.4 on SAS Viya. This includes topics such as exploring the data, building predictive models, assessing model performance, and deploying models. A00-274 exam also focuses on the use of SAS Viya, which is a cloud-based analytics platform that allows users to access and analyze data from any device.
SASInstitute A00-274 is an exam that is designed to evaluate the knowledge, skills, and abilities of candidates in building interactive models using SAS Visual Statistics 8.4 on SAS Viya. A00-274 exam is ideal for individuals who are interested in data analysis and modeling and want to enhance their skills in SAS Viya.
SASInstitute A00-274 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Model Comparison and Scoring | 9% | - Compare multiple models using appropriate metrics - Apply models to score new data - Interpret scoring results |
| SAS Visual Statistics Cross-Functional Tasks | 22% | - Perform model validation - Use interactive group-by functionality - Prepare data using SAS Visual Analytics - Filter data for modeling |
| Building and Assessing Regression-Type Models | 41% | - Explain linear model concepts and assumptions - Evaluate linear regression model results - Interpret and validate regression model outputs - Perform linear regression modeling - Perform nonparametric logistic regression modeling - Build generalized additive models |
| Building and Assessing Segmentation Models | 28% | - Unsupervised segmentation using cluster analysis - Supervised segmentation using decision trees - Interpret and analyze cluster results - Assess and interpret decision tree performance |
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