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Last Updated: Oct 09, 2026
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SASInstitute A00-255 Exam Overview:
| Certification Vendor: | SAS Institute |
|---|---|
| Exam Name: | Predictive Modeling Using SAS Enterprise Miner 14 |
| Exam Number: | A00-255 |
| Passing Score: | Approximately 68-70% |
| Related Certifications: | SAS Certified Advanced Analytics Professional SAS Certified Data Scientist |
| Available Languages: | English |
| Exam Duration: | 110 minutes |
| Certificate Validity Period: | 3 years |
| Exam Format: | Multiple Choice |
| Real Exam Qty: | 60-65 |
| Exam Price: | $180 USD |
| Recommended Training: | SAS e-Learning Courses SAS Predictive Modeling Using Enterprise Miner Training |
| Exam Registration: | Pearson VUE Exam Registration SAS Certification Registration |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Delivered via Pearson VUE (online proctored or test center) |
| Pre Condition: | No mandatory prerequisite exam; recommended experience with SAS Enterprise Miner and predictive modeling concepts |
| Official Syllabus URL: | https://www.sas.com/en_us/certification.html |
SASInstitute A00-255 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Exploratory Data Analysis | - Descriptive statistics and data profiling - Visualization techniques for pattern discovery |
| Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
| Model Development | - Decision trees and ensemble methods - Regression modeling techniques - Neural networks and advanced modeling in SAS Enterprise Miner |
| Data Understanding and Preparation | - Feature selection and transformation - Handling missing values and outliers - Data collection and data source identification - Data cleaning and preprocessing |
| Model Implementation and Deployment | - Model scoring and deployment in SAS Enterprise Miner - Monitoring model performance in production |
| Model Evaluation and Validation | - Model comparison and selection - Model performance metrics - Validation and cross-validation techniques |
The SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Exam: Clear Answers
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SASInstitute recommends these training resources for candidates:
Official courses supply the theory; distilled practice material with verified answers supplies the exam craft. Both belong in a serious plan.
No mandatory prerequisite exam; recommended experience with SAS Enterprise Miner and predictive modeling concepts
A dedicated team of experts compiles the SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 question bank and maintains it continuously: new questions are added as the exam evolves in the market, and the content is recomposed against the latest syllabus and trends. Difficult topics are distilled into clear, study-friendly form, and every answer is expert-verified. The A00-255 exam bank you buy is a living product, not a frozen file.
The A00-255 exam is the official assessment behind the SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 certification from SASInstitute. Credentials like this carry weight because they demonstrate something specific: the ability to solve problems under pressure, verified by an independent exam. In a competitive field, that visible proof of skill is what helps a candidate stand out — and thorough preparation is what earns it.
Passing the A00-255 exam requires Approximately 68-70%, and registration costs $180 USD. Success takes perspiration — and a smart way to spend it, which is exactly what objective-aligned practice with verified answers provides.
The official outline divides the A00-255 exam into weighted domains, including:
- Model Evaluation and Validation ()
- Business Understanding and Analytical Framework ()
- Model Implementation and Deployment ()
The SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 bank at SureTorrent is recomposed against this syllabus whenever it shifts, so the material tracks the exam's own direction.
Registration for the A00-255 exam runs through these official channels:
Book when your practice scores hold steady — effort is best spent before the date, not after it.
The A00-255 exam contains 60-65 questions with 110 minutes minutes to complete them. Solving problems under time pressure is a skill of its own — and timed practice is how you build it.
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
The number of parameters (weights) estimated by the Neural Network model is in which of the following ranges?
Response:
- A. 11-15
- B. 6-10
- C. 16 or more
- D. less than or equal to 5
Correct Answer: C 🗳️
1. Define a new data source, PatternData, in SAS Enterprise Miner (SAS data set Patterndata.sas7bdat in the zip file distributed with this practice exam).
2. Set the role of all variables to Input, with the exception set the ID variable role to ID.
3. Set the measurement level for all variables to Interval, except:
- Set DemHomeOwner and StatusCatStarAll to Binary.
- Set DemCluster, DemGender, ID, and StatusCat96NK to Nominal.
4. Create a new diagram (name it Section6) within the project labeled Test.
5. Add the data source, PatternData, to this diagram. Make sure the variable roles and measurements are the same as in the table below. (Check the highlighted rows carefully and reset roles/levels as needed.)
6. Connect a Cluster node to the data source.
7. Modify the Cluster node to exclude nominal and binary input variables.
8. Run the Cluster node.
How many clusters are created by the Cluster node?
Response:
- A. 8
- B. 3
- C. 6
- D. 9
Correct Answer: B 🗳️
Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:
- A. Cluster
- B. Random
- C. Systemic
- D. Stratify
Correct Answer: D 🗳️
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:
- A. reduction of odds for TARGET=1 by 0.3457
- B. change of odds for TARGET=1 by a factor 0.708
- C. reduction of odds for TARGET=1 by 0.708
- D. change of odds for TARGET=1 by a factor 0.3457
Correct Answer: B 🗳️
Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:
- A. Sample Method: Stratify and Criterion: Equal
- B. Sample Method: Stratify and Criterion: Proportional
- C. Sample Method: Random and Criterion: Equal
- D. Sample Method: Random and Criterion: Proportional
Correct Answer: A 🗳️
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