WGU D491 INTRODUCTION TO ANALYTICS OA EXAM AND
STUDY GUIDE NEWEST 2025-2026 ACTUAL EXAM 250
QUESTIONS AND CORRECT DETAILED ANSWERS
(VERIFIED ANSWERS) |ALREADY GRADED A+
✅ Key Features
250 real exam-based questions with verified correct answers.
Detailed rationales/explanations for every answer.
Newest 2025–2026 edition, aligned with WGU’s D491 OA exam
requirements.
Verified accuracy and graded A+ quality.
Comprehensive coverage for Introduction to Analytics exam success.
🎯 Who This Resource Is For
WGU students preparing for the D491 Introduction to Analytics OA
Exam.
Learners wanting in-depth practice with rationales for stronger
understanding.
Mentors, tutors, and educators seeking a reliable test prep resource.
Candidates aiming for exam readiness and verified study support.
What is data analytics?
- The process of analyzing data to extract insights
- The process of encrypting data to keep it secure
- The process of storing data in a secure location for future use
- The process of collecting data from various sources - answer-The process of analyzing data to extract
insights
What is data science?
- The practice of using statistical methods to extract insights from data
- A field that involves creating data visualizations to provide insights
,- The process of creating computer programs to automate tasks
- The study of how computers interact with human language - answer-The practice of using statistical
methods to extract insights from data
How is data science different from data analytics?
- Data science focuses more on tracking experimental data, and data analytics is based on statistical
methods and hypotheses.
- Data science focuses on developing new algorithms and models, while data analytics focuses on using
existing models to analyze data.
- Data science focuses more on data visualization, while data analytics focuses on data cleaning and
preprocessing.
- Data science involves creating new algorithms, while data analytics uses existing statistical methods. -
answer-Data science focuses on developing new algorithms and models, while data analytics focuses
on using existing models to analyze data.
Which comparison describes the difference between data analytics and data science?
- Data analytics focuses on descriptive analysis, while data science focuses on prescriptive analysis.
- Data analytics is the process of analyzing data to extract insights, while data science involves building
and testing models to make predictions.
- Data analytics focuses on statistics, and data science mainly focuses on qualitative reasoning.
- Data science involves analyzing data from structured sources, while data analytics involves analyzing
data from unstructured sources. - answer-Data analytics is the process of analyzing data to extract
insights, while data science involves building and testing models to make predictions.
Which type of data analytics project aims to determine why something happened in the past?
- Diagnostic
- Descriptive
- Predictive
- Prescriptive - answer-Descriptive
What are the different types of data analytics projects?Descriptive, diagnostic, predictive, and
prescriptive analytics
,- Data warehousing, data mining, data visualization, and business intelligence
- Regression analysis, time series analysis, text analytics, and network analysis
- Data collection, data cleaning, data transformation, and data visualization
- Descriptive, diagnostic, predictive, and prescriptive analytics - answer-Descriptive, diagnostic,
predictive, and prescriptive analytics
What is the difference between exploratory and confirmatory data analytics projects?
- Exploratory projects involve testing hypotheses and finding patterns in data, while confirmatory
projects involve verifying existing hypotheses.
- Exploratory projects involve analyzing data that is already structured, while confirmatory projects
involve analyzing unstructured data.
- Exploratory projects involve analyzing large datasets, while confirmatory projects involve analyzing
smaller datasets.
- Exploratory projects involve analyzing data from a single source, while confirmatory projects involve
integrating data from multiple sources. - answer-Exploratory projects involve testing hypotheses and
finding patterns in data, while confirmatory projects involve verifying existing hypotheses.
NOT CORRECT
Which project is considered a data analytics project?
- Developing a recommendation system to suggest new products to customers based on their past
purchases
- Creating a dashboard to visualize sales data and monitor inventory levels for a grocery store chain
- Building a predictive model to forecast stock prices for a financial services company
- Designing a database schema to store customer information for a retail store - answer-Creating a
dashboard to visualize sales data and monitor inventory levels for a grocery store chain
Why is quality control/assurance crucial for data engineers in a data analytics project?
- It ensures that the data is analyzed in a timely manner.
- It ensures that the data is stored in a secure location.
- It ensures that the data is accurate and reliable.
- It ensures that the data is accessible to all stakeholders. - answer-It ensures that the data is accurate
and reliable.
, What does a data analyst do in a data analytics project?
- Conducts exploratory data analysis to identify trends and patterns
- Focuses on building machine learning models
- Oversees data governance and data quality assurance
- Designs and develops databases and data pipelines - answer-Conducts exploratory data analysis to
identify trends and patterns
What is the function of a data scientist in an organization?
- To design and maintain data visualizations and dashboards
- To oversee data governance and compliance
- To work independently to analyze data and make decisions based on their findings
- To conduct statistical analysis and machine learning modeling - answer-To conduct statistical analysis
and machine learning modeling
What is the role of a business intelligence analyst?
- Overseeing data governance and compliance
- Developing and implementing data processing pipelines
- Designing and maintaining data visualizations and dashboards
- Conducting statistical analysis and machine learning modeling - answer-Designing and maintaining data
visualizations and dashboards
What is a primary responsibility of a data engineer?
- Designing and implementing data storage solutions
- Designing and developing data visualizations for stakeholders
- Analyzing and interpreting data to inform business decisions
- Developing predictive models using machine learning algorithms - answer-Designing and implementing
data storage solutions
What is a primary responsibility of a machine learning engineer?
STUDY GUIDE NEWEST 2025-2026 ACTUAL EXAM 250
QUESTIONS AND CORRECT DETAILED ANSWERS
(VERIFIED ANSWERS) |ALREADY GRADED A+
✅ Key Features
250 real exam-based questions with verified correct answers.
Detailed rationales/explanations for every answer.
Newest 2025–2026 edition, aligned with WGU’s D491 OA exam
requirements.
Verified accuracy and graded A+ quality.
Comprehensive coverage for Introduction to Analytics exam success.
🎯 Who This Resource Is For
WGU students preparing for the D491 Introduction to Analytics OA
Exam.
Learners wanting in-depth practice with rationales for stronger
understanding.
Mentors, tutors, and educators seeking a reliable test prep resource.
Candidates aiming for exam readiness and verified study support.
What is data analytics?
- The process of analyzing data to extract insights
- The process of encrypting data to keep it secure
- The process of storing data in a secure location for future use
- The process of collecting data from various sources - answer-The process of analyzing data to extract
insights
What is data science?
- The practice of using statistical methods to extract insights from data
- A field that involves creating data visualizations to provide insights
,- The process of creating computer programs to automate tasks
- The study of how computers interact with human language - answer-The practice of using statistical
methods to extract insights from data
How is data science different from data analytics?
- Data science focuses more on tracking experimental data, and data analytics is based on statistical
methods and hypotheses.
- Data science focuses on developing new algorithms and models, while data analytics focuses on using
existing models to analyze data.
- Data science focuses more on data visualization, while data analytics focuses on data cleaning and
preprocessing.
- Data science involves creating new algorithms, while data analytics uses existing statistical methods. -
answer-Data science focuses on developing new algorithms and models, while data analytics focuses
on using existing models to analyze data.
Which comparison describes the difference between data analytics and data science?
- Data analytics focuses on descriptive analysis, while data science focuses on prescriptive analysis.
- Data analytics is the process of analyzing data to extract insights, while data science involves building
and testing models to make predictions.
- Data analytics focuses on statistics, and data science mainly focuses on qualitative reasoning.
- Data science involves analyzing data from structured sources, while data analytics involves analyzing
data from unstructured sources. - answer-Data analytics is the process of analyzing data to extract
insights, while data science involves building and testing models to make predictions.
Which type of data analytics project aims to determine why something happened in the past?
- Diagnostic
- Descriptive
- Predictive
- Prescriptive - answer-Descriptive
What are the different types of data analytics projects?Descriptive, diagnostic, predictive, and
prescriptive analytics
,- Data warehousing, data mining, data visualization, and business intelligence
- Regression analysis, time series analysis, text analytics, and network analysis
- Data collection, data cleaning, data transformation, and data visualization
- Descriptive, diagnostic, predictive, and prescriptive analytics - answer-Descriptive, diagnostic,
predictive, and prescriptive analytics
What is the difference between exploratory and confirmatory data analytics projects?
- Exploratory projects involve testing hypotheses and finding patterns in data, while confirmatory
projects involve verifying existing hypotheses.
- Exploratory projects involve analyzing data that is already structured, while confirmatory projects
involve analyzing unstructured data.
- Exploratory projects involve analyzing large datasets, while confirmatory projects involve analyzing
smaller datasets.
- Exploratory projects involve analyzing data from a single source, while confirmatory projects involve
integrating data from multiple sources. - answer-Exploratory projects involve testing hypotheses and
finding patterns in data, while confirmatory projects involve verifying existing hypotheses.
NOT CORRECT
Which project is considered a data analytics project?
- Developing a recommendation system to suggest new products to customers based on their past
purchases
- Creating a dashboard to visualize sales data and monitor inventory levels for a grocery store chain
- Building a predictive model to forecast stock prices for a financial services company
- Designing a database schema to store customer information for a retail store - answer-Creating a
dashboard to visualize sales data and monitor inventory levels for a grocery store chain
Why is quality control/assurance crucial for data engineers in a data analytics project?
- It ensures that the data is analyzed in a timely manner.
- It ensures that the data is stored in a secure location.
- It ensures that the data is accurate and reliable.
- It ensures that the data is accessible to all stakeholders. - answer-It ensures that the data is accurate
and reliable.
, What does a data analyst do in a data analytics project?
- Conducts exploratory data analysis to identify trends and patterns
- Focuses on building machine learning models
- Oversees data governance and data quality assurance
- Designs and develops databases and data pipelines - answer-Conducts exploratory data analysis to
identify trends and patterns
What is the function of a data scientist in an organization?
- To design and maintain data visualizations and dashboards
- To oversee data governance and compliance
- To work independently to analyze data and make decisions based on their findings
- To conduct statistical analysis and machine learning modeling - answer-To conduct statistical analysis
and machine learning modeling
What is the role of a business intelligence analyst?
- Overseeing data governance and compliance
- Developing and implementing data processing pipelines
- Designing and maintaining data visualizations and dashboards
- Conducting statistical analysis and machine learning modeling - answer-Designing and maintaining data
visualizations and dashboards
What is a primary responsibility of a data engineer?
- Designing and implementing data storage solutions
- Designing and developing data visualizations for stakeholders
- Analyzing and interpreting data to inform business decisions
- Developing predictive models using machine learning algorithms - answer-Designing and implementing
data storage solutions
What is a primary responsibility of a machine learning engineer?
