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WGU D491 INTRODUCTION TO ANALYTICS OA
EXAM LATEST 2024 WITHUPDATED QUESTIONS
AND DETAILED CORRECT ANSWERS WITH
RATIONALES (ALREADY GRADED A+)
In which phase of the data mining process does the data science team
investigate the problem, develop context and understanding, learn about
available data sources, and formulate initial hypotheses?
-Data preparation
-Model planning
-Model execution
-Discovery - ANSWER-Discovery (This is the stage where the team delves
into the problem, gains insights, learns about the data that can be used, and
comes up with initial ideas to be tested with the data.)
,2|Page
What is the primary purpose of the discovery phase in the data science
process?
-To develop interactive visualizations for stakeholder presentations
-To evaluate and optimize data-driven predictive models
-To clean and preprocess the data for analysis
-To understand the business problem and develop initial hypotheses -
ANSWER-To understand the business problem and develop initial
hypotheses. (This phase focuses on investigating the issue, gaining a deeper
understanding of the context, learning about available data sources, and
formulating initial ideas that will be tested using data.)
ETLT - ANSWER-Extract, Transform, Load, Transform
Which question of interest is appropriate for a data analytics project to
increase a store's sales?
-Which customer segments will most likely respond to a marketing
campaign?
-Should the store expand to a new location?
-How can the store's social media presence be improved?
-What are the store's best-selling products? - ANSWER-Which customer
segments will most likely respond to a marketing campaign? (This question
focuses on identifying customer segments most likely to respond positively to
,3|Page
a marketing campaign, directly addressing the goal of increasing sales. By
targeting the right customer segments, the store can optimize its marketing
efforts and increase its overall sales.)
A data analyst works at an e-commerce company that wants to understand
its customer churn rate. Their manager has tasked them with conducting a
data analytics project to identify customers at risk of churn and offer these
customers targeted promotions to retain their business.
What is the primary purpose of the data analytics project's results in this
scenario?
-To identify customer preferences
-To predict customer churn risk
-To optimize inventory management
-To compare the company's churn rate to industry benchmarks - ANSWER-
To predict customer churn risk (The project aims to predict which customers
are likely to leave the company so that targeted promotions can be offered to
retain their business.)
A data analyst works at an e-commerce company that wants to understand
its customer churn rate. Their manager has tasked them with conducting a
data analytics project to identify customers at risk of churn and offer these
, 4|Page
customers targeted promotions to retain their business.
What is the most suitable form of deliverable in this scenario?
-Updated website design
-Supply chain improvements
-Lists of at-risk customers
-Monthly sales reports - ANSWER-Lists of at-risk customers (Providing a list
of at-risk customers for targeted marketing campaigns can help retain their
business and prevent revenue loss.)
A retail company wants to improve its sales and customer satisfaction by
analyzing customer data. The company hired a data analytics team, which
has access to the company's customer database, including transaction
records, demographic information, and customer feedback. The data
analytics team will work closely with the marketing and IT departments to
create actionable insights for the company. The team has three months to
complete the project, and the company's budget allows purchasing additional
software tools or training, if necessary.
-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
WGU D491 INTRODUCTION TO ANALYTICS OA
EXAM LATEST 2024 WITHUPDATED QUESTIONS
AND DETAILED CORRECT ANSWERS WITH
RATIONALES (ALREADY GRADED A+)
In which phase of the data mining process does the data science team
investigate the problem, develop context and understanding, learn about
available data sources, and formulate initial hypotheses?
-Data preparation
-Model planning
-Model execution
-Discovery - ANSWER-Discovery (This is the stage where the team delves
into the problem, gains insights, learns about the data that can be used, and
comes up with initial ideas to be tested with the data.)
,2|Page
What is the primary purpose of the discovery phase in the data science
process?
-To develop interactive visualizations for stakeholder presentations
-To evaluate and optimize data-driven predictive models
-To clean and preprocess the data for analysis
-To understand the business problem and develop initial hypotheses -
ANSWER-To understand the business problem and develop initial
hypotheses. (This phase focuses on investigating the issue, gaining a deeper
understanding of the context, learning about available data sources, and
formulating initial ideas that will be tested using data.)
ETLT - ANSWER-Extract, Transform, Load, Transform
Which question of interest is appropriate for a data analytics project to
increase a store's sales?
-Which customer segments will most likely respond to a marketing
campaign?
-Should the store expand to a new location?
-How can the store's social media presence be improved?
-What are the store's best-selling products? - ANSWER-Which customer
segments will most likely respond to a marketing campaign? (This question
focuses on identifying customer segments most likely to respond positively to
,3|Page
a marketing campaign, directly addressing the goal of increasing sales. By
targeting the right customer segments, the store can optimize its marketing
efforts and increase its overall sales.)
A data analyst works at an e-commerce company that wants to understand
its customer churn rate. Their manager has tasked them with conducting a
data analytics project to identify customers at risk of churn and offer these
customers targeted promotions to retain their business.
What is the primary purpose of the data analytics project's results in this
scenario?
-To identify customer preferences
-To predict customer churn risk
-To optimize inventory management
-To compare the company's churn rate to industry benchmarks - ANSWER-
To predict customer churn risk (The project aims to predict which customers
are likely to leave the company so that targeted promotions can be offered to
retain their business.)
A data analyst works at an e-commerce company that wants to understand
its customer churn rate. Their manager has tasked them with conducting a
data analytics project to identify customers at risk of churn and offer these
, 4|Page
customers targeted promotions to retain their business.
What is the most suitable form of deliverable in this scenario?
-Updated website design
-Supply chain improvements
-Lists of at-risk customers
-Monthly sales reports - ANSWER-Lists of at-risk customers (Providing a list
of at-risk customers for targeted marketing campaigns can help retain their
business and prevent revenue loss.)
A retail company wants to improve its sales and customer satisfaction by
analyzing customer data. The company hired a data analytics team, which
has access to the company's customer database, including transaction
records, demographic information, and customer feedback. The data
analytics team will work closely with the marketing and IT departments to
create actionable insights for the company. The team has three months to
complete the project, and the company's budget allows purchasing additional
software tools or training, if necessary.
-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
