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INTRODUCTION TO ANALYTICS – WGU D491 (2026) | WITH VERIFIED QUESTIONS & ANSWERS

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INTRODUCTION TO ANALYTICS – WGU D491 (2026) | WITH VERIFIED QUESTIONS & ANSWERS

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INTRODUCTION TO ANALYTICS – WGU D491
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INTRODUCTION TO ANALYTICS – WGU D491

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INTRODUCTION TO ANALYTICS – WGU
D491 (2026) | WITH VERIFIED
QUESTIONS & ANSWERS




What is Data analytics?
-The process of encrypting data to keep it secure
-The process of storing data in a secure location for future use
-The process of analyzing data to extract insights
-The process of collecting data from various sources -
Answer The process of analyzing data to extract insights. (Data
analytics involves analyzing data to extract insights and inform
decision-making. This includes using various techniques and tools
to explore, clean, transform, and model data and visualize and
communicate findings.)


What is data science?
-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

,-The practice of using statistical methods to extract insights from
data - Answer The practice of using statistical methods to
extract insights from data. (Data science is a multidisciplinary field
involving various statistical, mathematical, and computational
methods to extract meaningful insights and knowledge from data.)


How is data science different from data analytics?
-Data science focuses more on data visualization, while data
analytics focuses on data cleaning and preprocessing.
-Data science focuses more on tracking experimental data, and
data analytics is based on statistical methods and hypotheses.
-Data science involves creating new algorithms, while data analytics
uses existing statistical methods.
-Data science focuses on developing new algorithms and models,
while data analytics focuses on using existing models to analyze
data. - Answer Data science focuses on developing new
algorithms and models, while data analytics focuses on using
existing models to analyze data. (Data science is more research-
based, while data analytics is more focused on the practical
applications of data analytics.)


Which comparison describes the difference between data analytics
and data science?
-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.
-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 descriptive analysis, while data science
focuses on prescriptive analysis. - Answer Data analytics is
the process of analyzing data to extract insights, while data science
involves building and testing models to make predictions. (Data
analytics involves using statistical and quantitative methods to
analyze data to extract insights and solve problems, while data
science involves using machine learning and statistical models to
build predictive models and make decisions based on data.)


Which type of data analytics project aims to determine why
something happened in the past?
-Prescriptive
-Descriptive
-Predictive

-Diagnostic - Answer Descriptive (Descriptive analytics
focuses on summarizing past events and understanding what
happened.)


What are the different types of data analytics projects?

, -Regression analysis, time series analysis, text analytics, and
network analysis
-Data warehousing, data mining, data visualization, and business
intelligence
-Descriptive, diagnostic, predictive, and prescriptive analytics
-Data collection, data cleaning, data transformation, and data
visualization - 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 from a single source,
while confirmatory projects involve integrating data from multiple
sources.
-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. -
Answer Exploratory projects involve testing hypotheses and
finding patterns in data, while confirmatory projects involve verifying
existing hypotheses. (Exploratory data analytics projects are
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