WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
WGU D491 INTRODUCTION TO ANALYTICS OBJECTIVE ASSESSMENT
FINAL EXAM VERSION 1 ACTUAL EXAM NEWEST 2025/2026 WITH
COMPLETE QUESTIONS AND CORRECT ANSWERS |ALREADY GRADED
A+||BRAND NEW VERSION!
In the data analytics process, which phase focuses on identifying candidate
models for clustering, classifying, or finding relationships and ensuring analytical
techniques align with business objectives?
Data transformation
Discovery
Model planning
Data preparation
Model planning
What is the primary purpose of the model planning phase in the data analytics
process?
- Identifying methods and aligning techniques with objectives
- Transforming data to bring information to the surface
- Cleaning and conditioning data for analysis
- Assessing resources and framing the business problem
Identifying methods and aligning techniques with objectives
Which activities should be the focus of the model planning phase?
- Transforming data to bring information to the surface
- Visualizing and exploring data patterns
- Cleaning and conditioning data for analysis
- Partitioning the data into training, validation, and test sets
1|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
Partitioning the data into training, validation, and test sets
During the data modeling phase, partitioning the dataset into training, validation,
and test sets is a crucial activity to build and assess the predictive model's
performance.
Which tool is commonly used during the model planning phase?
KNIME
OpenRefine
Hadoop
Data Wrangler
KNIME
KNIME is an open-source data analytics platform for visually creating data
workflows.
A healthcare company wants to predict which patients are at risk of developing a
certain medical condition. Which model is commonly used for this type of
analysis?
Decision tree
Association rules
K-means clustering
Logistic regression
Logistic regression
Logistic regression is a model that predicts the probability of an event occurring.
During a data analytics project, which phase focuses on developing training and
test datasets, refining models, and assessing the validity and predictive power of
the models?
2|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
Model execution
Data preparation
Model planning
Operationalize
Model execution
What is the main purpose of the model execution phase in a data analytics
project?
To clean, transform, and aggregate data for analysis
To develop datasets, refine models, and assess validity
To select appropriate models based on project goals
To deploy the model and calculate its financial impact
To develop datasets, refine models, and assess validity
Which activities should the data analytics team perform during the model
execution phase of this project?
- Creating data visualizations and capturing essential predictors
- Deploying the model and measuring its return on investment
- Generating training and test sets and refining models to enhance performance
- Grouping categorical variables and standardizing numeric values
Generating training and test sets and refining models to enhance performance
Which tool is suitable for a data analytics team to use during the model execution
phase of a project?
SAS Enterprise Miner
Tableau
KNIME
Microsoft Excel
3|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
SAS Enterprise Miner
Which phase of a data analytics project involves articulating findings and
outcomes for stakeholders while considering caveats, assumptions, and
limitations?
Data preparation
Communicate results
Operationalize
Model development
Communicate results
What is the purpose of the communicate results phase in a data analytics project?
Presenting findings and outcomes to stakeholders
Preparing and managing data for analysis
Evaluating the project's financial and technical results
Creating and refining analytical models
Presenting findings and outcomes to stakeholders
Which activity should the data analytics team focus on during the communicate
results phase
- Presenting key findings to stakeholders and evaluating the project's success
- Building and testing different predictive models for customer churn
- Analyzing the financial impact of the project on the company's revenue and
customer retention
- Performing data cleaning and transforming raw data into usable formats
Presenting key findings to stakeholders and evaluating the project's success
Which tools are commonly used for communicating results in data analytics
projects?
4|Page
Version 1
WGU D491 INTRODUCTION TO ANALYTICS OBJECTIVE ASSESSMENT
FINAL EXAM VERSION 1 ACTUAL EXAM NEWEST 2025/2026 WITH
COMPLETE QUESTIONS AND CORRECT ANSWERS |ALREADY GRADED
A+||BRAND NEW VERSION!
In the data analytics process, which phase focuses on identifying candidate
models for clustering, classifying, or finding relationships and ensuring analytical
techniques align with business objectives?
Data transformation
Discovery
Model planning
Data preparation
Model planning
What is the primary purpose of the model planning phase in the data analytics
process?
- Identifying methods and aligning techniques with objectives
- Transforming data to bring information to the surface
- Cleaning and conditioning data for analysis
- Assessing resources and framing the business problem
Identifying methods and aligning techniques with objectives
Which activities should be the focus of the model planning phase?
- Transforming data to bring information to the surface
- Visualizing and exploring data patterns
- Cleaning and conditioning data for analysis
- Partitioning the data into training, validation, and test sets
1|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
Partitioning the data into training, validation, and test sets
During the data modeling phase, partitioning the dataset into training, validation,
and test sets is a crucial activity to build and assess the predictive model's
performance.
Which tool is commonly used during the model planning phase?
KNIME
OpenRefine
Hadoop
Data Wrangler
KNIME
KNIME is an open-source data analytics platform for visually creating data
workflows.
A healthcare company wants to predict which patients are at risk of developing a
certain medical condition. Which model is commonly used for this type of
analysis?
Decision tree
Association rules
K-means clustering
Logistic regression
Logistic regression
Logistic regression is a model that predicts the probability of an event occurring.
During a data analytics project, which phase focuses on developing training and
test datasets, refining models, and assessing the validity and predictive power of
the models?
2|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
Model execution
Data preparation
Model planning
Operationalize
Model execution
What is the main purpose of the model execution phase in a data analytics
project?
To clean, transform, and aggregate data for analysis
To develop datasets, refine models, and assess validity
To select appropriate models based on project goals
To deploy the model and calculate its financial impact
To develop datasets, refine models, and assess validity
Which activities should the data analytics team perform during the model
execution phase of this project?
- Creating data visualizations and capturing essential predictors
- Deploying the model and measuring its return on investment
- Generating training and test sets and refining models to enhance performance
- Grouping categorical variables and standardizing numeric values
Generating training and test sets and refining models to enhance performance
Which tool is suitable for a data analytics team to use during the model execution
phase of a project?
SAS Enterprise Miner
Tableau
KNIME
Microsoft Excel
3|Page
, WGU D491 Introduction To Analytics Objective Assessment Final Exam
Version 1
SAS Enterprise Miner
Which phase of a data analytics project involves articulating findings and
outcomes for stakeholders while considering caveats, assumptions, and
limitations?
Data preparation
Communicate results
Operationalize
Model development
Communicate results
What is the purpose of the communicate results phase in a data analytics project?
Presenting findings and outcomes to stakeholders
Preparing and managing data for analysis
Evaluating the project's financial and technical results
Creating and refining analytical models
Presenting findings and outcomes to stakeholders
Which activity should the data analytics team focus on during the communicate
results phase
- Presenting key findings to stakeholders and evaluating the project's success
- Building and testing different predictive models for customer churn
- Analyzing the financial impact of the project on the company's revenue and
customer retention
- Performing data cleaning and transforming raw data into usable formats
Presenting key findings to stakeholders and evaluating the project's success
Which tools are commonly used for communicating results in data analytics
projects?
4|Page
