WGU - Introduction to Analytics D491
1. What is data analytics? The process of analyzing
data to extract insights
- The process of analyzing data to extract in-
sights
- The process of encrypting data to keep it
secure
- The process of storing data in a secure loca-
tion for future use
- The process of collecting data from various
sources
2. What is data science? The practice of using sta-
tistical methods to extract
- The practice of using statistical methods to insights from data
extract insights from data
- A field that involves creating data visualiza-
tions to provide insights
- The process of creating computer programs
to automate tasks
- The study of how computers interact with
human language
3. How is data science different from data analyt- Data science focuses
ics? on developing new algo-
rithms and models, while
- Data science focuses more on tracking ex- data analytics focuses on
perimental data, and data analytics is based using existing models to
on statistical methods and hypotheses. analyze data.
- 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 visual-
ization, while data analytics focuses on data
cleaning and preprocessing.
- Data science involves creating new algo-
rithms, while data analytics uses existing sta-
tistical methods.
, WGU - Introduction to Analytics D491
4. Which comparison describes the difference Data analytics is the
between data analytics and data science? process of analyzing data
to extract insights, while
- Data analytics focuses on descriptive analy- data science involves
sis, while data science focuses on prescrip- building and testing mod-
tive analysis. els to make predictions.
- 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 reason-
ing.
- Data science involves analyzing data from
structured sources, while data analytics in-
volves analyzing data from unstructured
sources.
5. Which type of data analytics project aims to Diagnostic
determine why something happened in the
past?
- Diagnostic
- Descriptive
- Predictive
- Prescriptive
6. What are the different types of data analytics Descriptive, diagnostic,
projects? predictive, and prescrip-
tive analytics
- Data warehousing, data mining, data visual-
ization, and business intelligence
- Regression analysis, time series analysis,
text analytics, and network analysis
- Data collection, data cleaning, data transfor-
mation, and data visualization
- Descriptive, diagnostic, predictive, and pre-
scriptive analytics
, WGU - Introduction to Analytics D491
7. What is the difference between exploratory Exploratory projects in-
and confirmatory data analytics projects? volve testing hypotheses
and finding patterns in
- Exploratory projects involve testing hypothe- data, while confirmatory
ses and finding patterns in data, while con- projects involve verifying
firmatory projects involve verifying existing existing hypotheses.
hypotheses. NOT CORRECT
- 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 pro-
jects involve integrating data from multiple
sources.
8. Which project is considered a data analytics Creating a dashboard to
project? visualize sales data and
monitor inventory levels
- Developing a recommendation system to for a grocery store chain
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 cus-
tomer information for a retail store
9. Why is quality control/assurance crucial for It ensures that the data is
data engineers in a data analytics project? accurate and reliable.
- It ensures that the data is analyzed in a timely
manner.
- It ensures that the data is stored in a secure
location.
, WGU - Introduction to Analytics D491
- It ensures that the data is accurate and reli-
able.
- It ensures that the data is accessible to all
stakeholders.
10. What does a data analyst do in a data analytics Conducts exploratory
project? data analysis to identify
trends and patterns
- Conducts exploratory data analysis to iden-
tify trends and patterns
- Focuses on building machine learning mod-
els
- Oversees data governance and data quality
assurance
- Designs and develops databases and data
pipelines
11. What is the function of a data scientist in an To conduct statistical
organization? analysis and machine
learning modeling
- 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
12. What is the role of a business intelligence Designing and maintain-
analyst? ing data visualizations and
- Overseeing data governance and compli- dashboards
ance
- Developing and implementing data process-
ing pipelines
- Designing and maintaining data visualiza-
tions and dashboards
- Conducting statistical analysis and machine
learning modeling
13.
1. What is data analytics? The process of analyzing
data to extract insights
- The process of analyzing data to extract in-
sights
- The process of encrypting data to keep it
secure
- The process of storing data in a secure loca-
tion for future use
- The process of collecting data from various
sources
2. What is data science? The practice of using sta-
tistical methods to extract
- The practice of using statistical methods to insights from data
extract insights from data
- A field that involves creating data visualiza-
tions to provide insights
- The process of creating computer programs
to automate tasks
- The study of how computers interact with
human language
3. How is data science different from data analyt- Data science focuses
ics? on developing new algo-
rithms and models, while
- Data science focuses more on tracking ex- data analytics focuses on
perimental data, and data analytics is based using existing models to
on statistical methods and hypotheses. analyze data.
- 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 visual-
ization, while data analytics focuses on data
cleaning and preprocessing.
- Data science involves creating new algo-
rithms, while data analytics uses existing sta-
tistical methods.
, WGU - Introduction to Analytics D491
4. Which comparison describes the difference Data analytics is the
between data analytics and data science? process of analyzing data
to extract insights, while
- Data analytics focuses on descriptive analy- data science involves
sis, while data science focuses on prescrip- building and testing mod-
tive analysis. els to make predictions.
- 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 reason-
ing.
- Data science involves analyzing data from
structured sources, while data analytics in-
volves analyzing data from unstructured
sources.
5. Which type of data analytics project aims to Diagnostic
determine why something happened in the
past?
- Diagnostic
- Descriptive
- Predictive
- Prescriptive
6. What are the different types of data analytics Descriptive, diagnostic,
projects? predictive, and prescrip-
tive analytics
- Data warehousing, data mining, data visual-
ization, and business intelligence
- Regression analysis, time series analysis,
text analytics, and network analysis
- Data collection, data cleaning, data transfor-
mation, and data visualization
- Descriptive, diagnostic, predictive, and pre-
scriptive analytics
, WGU - Introduction to Analytics D491
7. What is the difference between exploratory Exploratory projects in-
and confirmatory data analytics projects? volve testing hypotheses
and finding patterns in
- Exploratory projects involve testing hypothe- data, while confirmatory
ses and finding patterns in data, while con- projects involve verifying
firmatory projects involve verifying existing existing hypotheses.
hypotheses. NOT CORRECT
- 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 pro-
jects involve integrating data from multiple
sources.
8. Which project is considered a data analytics Creating a dashboard to
project? visualize sales data and
monitor inventory levels
- Developing a recommendation system to for a grocery store chain
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 cus-
tomer information for a retail store
9. Why is quality control/assurance crucial for It ensures that the data is
data engineers in a data analytics project? accurate and reliable.
- It ensures that the data is analyzed in a timely
manner.
- It ensures that the data is stored in a secure
location.
, WGU - Introduction to Analytics D491
- It ensures that the data is accurate and reli-
able.
- It ensures that the data is accessible to all
stakeholders.
10. What does a data analyst do in a data analytics Conducts exploratory
project? data analysis to identify
trends and patterns
- Conducts exploratory data analysis to iden-
tify trends and patterns
- Focuses on building machine learning mod-
els
- Oversees data governance and data quality
assurance
- Designs and develops databases and data
pipelines
11. What is the function of a data scientist in an To conduct statistical
organization? analysis and machine
learning modeling
- 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
12. What is the role of a business intelligence Designing and maintain-
analyst? ing data visualizations and
- Overseeing data governance and compli- dashboards
ance
- Developing and implementing data process-
ing pipelines
- Designing and maintaining data visualiza-
tions and dashboards
- Conducting statistical analysis and machine
learning modeling
13.
