WGU C207 DATA-DRIVEN DECISION MAKING EXAM
2026/2027 | Latest Update Guide | Verified Answers 100%
Correct | Pass Guaranteed - A+ Graded
SECTION 1: ANALYTICS TYPES & BUSINESS INTELLIGENCE
(QUESTIONS 1–12)
Question 1
A retail company analyzes last quarter's sales figures to determine which products had
the highest revenue. This is an example of which type of analytics?
A. Diagnostic analytics
B. Predictive analytics
C. Descriptive analytics
D. Prescriptive analytics
Correct Answer: C
Rationale: Descriptive analytics answers "what happened?" by summarizing historical
data. Analyzing past sales figures to identify top-performing products is purely
retrospective description. Diagnostic analytics (A) would investigate why certain
products performed well; predictive analytics (B) would forecast future sales;
prescriptive analytics (D) would recommend actions to optimize future performance.
This reflects the foundational analytics hierarchy taught in WGU C207.
Question 2
,A hospital analyzes patient readmission data and discovers that readmissions spike 72
hours after discharge when patients lack follow-up appointments. This analysis, which
identifies the root cause of a past problem, is BEST classified as:
A. Predictive analytics
B. Prescriptive analytics
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: C
Rationale: Diagnostic analytics answers "why did it happen?" through root cause
analysis. Identifying the causal link between lack of follow-up appointments and
readmission spikes moves beyond mere description to explain underlying factors.
Predictive analytics (A) would forecast future readmissions; prescriptive analytics (B)
would recommend specific interventions; descriptive analytics (D) would simply report
readmission rates without causal investigation. This reflects WGU C207 diagnostic
analytics competency.
Question 3
A financial institution uses machine learning algorithms to forecast the probability of
loan default based on borrower credit history, income, and debt-to-income ratio. This
represents:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: C
,Rationale: Predictive analytics answers "what will happen?" using statistical models and
forecasting techniques. Calculating loan default probability based on historical patterns
and borrower characteristics is classic predictive modeling. Descriptive (A) and
diagnostic (B) analytics are retrospective; prescriptive analytics (D) would recommend
whether to approve or deny the loan. This reflects WGU C207 predictive analytics and
probability application.
Question 4
A logistics company implements an optimization algorithm that determines the most
efficient delivery routes in real-time, considering traffic, fuel costs, and delivery windows.
This is an example of:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: D
Rationale: Prescriptive analytics answers "what should we do?" by providing actionable
recommendations and optimization solutions. Real-time route optimization that actively
recommends the best course of action goes beyond prediction to prescription.
Descriptive (A) would report past delivery times; diagnostic (B) would analyze why
delays occurred; predictive (C) would forecast traffic conditions. This reflects WGU
C207 prescriptive analytics and optimization principles.
Question 5
, A manufacturing firm maintains a centralized repository that integrates historical
production data, quality metrics, and supply chain information from multiple operational
systems. This repository is BEST described as a:
A. Data lake
B. Data mart
C. Data warehouse
D. OLAP cube
Correct Answer: C
Rationale: A data warehouse is a centralized, integrated repository of historical data
from multiple sources, optimized for query and analysis (not transaction processing). It
uses ETL (Extract, Transform, Load) processes to consolidate data. A data lake (A)
stores raw data in native formats; a data mart (B) is a subset focused on a specific
business function; an OLAP cube (D) is a multidimensional structure for analysis, not a
storage repository. This reflects WGU C207 business intelligence architecture.
Question 6
A marketing department creates a focused database containing only customer
demographic and campaign response data for the past two years. This subset of the
enterprise data warehouse is BEST called a:
A. Data lake
B. Data mart
C. Data warehouse
D. Operational database
Correct Answer: B
2026/2027 | Latest Update Guide | Verified Answers 100%
Correct | Pass Guaranteed - A+ Graded
SECTION 1: ANALYTICS TYPES & BUSINESS INTELLIGENCE
(QUESTIONS 1–12)
Question 1
A retail company analyzes last quarter's sales figures to determine which products had
the highest revenue. This is an example of which type of analytics?
A. Diagnostic analytics
B. Predictive analytics
C. Descriptive analytics
D. Prescriptive analytics
Correct Answer: C
Rationale: Descriptive analytics answers "what happened?" by summarizing historical
data. Analyzing past sales figures to identify top-performing products is purely
retrospective description. Diagnostic analytics (A) would investigate why certain
products performed well; predictive analytics (B) would forecast future sales;
prescriptive analytics (D) would recommend actions to optimize future performance.
This reflects the foundational analytics hierarchy taught in WGU C207.
Question 2
,A hospital analyzes patient readmission data and discovers that readmissions spike 72
hours after discharge when patients lack follow-up appointments. This analysis, which
identifies the root cause of a past problem, is BEST classified as:
A. Predictive analytics
B. Prescriptive analytics
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: C
Rationale: Diagnostic analytics answers "why did it happen?" through root cause
analysis. Identifying the causal link between lack of follow-up appointments and
readmission spikes moves beyond mere description to explain underlying factors.
Predictive analytics (A) would forecast future readmissions; prescriptive analytics (B)
would recommend specific interventions; descriptive analytics (D) would simply report
readmission rates without causal investigation. This reflects WGU C207 diagnostic
analytics competency.
Question 3
A financial institution uses machine learning algorithms to forecast the probability of
loan default based on borrower credit history, income, and debt-to-income ratio. This
represents:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: C
,Rationale: Predictive analytics answers "what will happen?" using statistical models and
forecasting techniques. Calculating loan default probability based on historical patterns
and borrower characteristics is classic predictive modeling. Descriptive (A) and
diagnostic (B) analytics are retrospective; prescriptive analytics (D) would recommend
whether to approve or deny the loan. This reflects WGU C207 predictive analytics and
probability application.
Question 4
A logistics company implements an optimization algorithm that determines the most
efficient delivery routes in real-time, considering traffic, fuel costs, and delivery windows.
This is an example of:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: D
Rationale: Prescriptive analytics answers "what should we do?" by providing actionable
recommendations and optimization solutions. Real-time route optimization that actively
recommends the best course of action goes beyond prediction to prescription.
Descriptive (A) would report past delivery times; diagnostic (B) would analyze why
delays occurred; predictive (C) would forecast traffic conditions. This reflects WGU
C207 prescriptive analytics and optimization principles.
Question 5
, A manufacturing firm maintains a centralized repository that integrates historical
production data, quality metrics, and supply chain information from multiple operational
systems. This repository is BEST described as a:
A. Data lake
B. Data mart
C. Data warehouse
D. OLAP cube
Correct Answer: C
Rationale: A data warehouse is a centralized, integrated repository of historical data
from multiple sources, optimized for query and analysis (not transaction processing). It
uses ETL (Extract, Transform, Load) processes to consolidate data. A data lake (A)
stores raw data in native formats; a data mart (B) is a subset focused on a specific
business function; an OLAP cube (D) is a multidimensional structure for analysis, not a
storage repository. This reflects WGU C207 business intelligence architecture.
Question 6
A marketing department creates a focused database containing only customer
demographic and campaign response data for the past two years. This subset of the
enterprise data warehouse is BEST called a:
A. Data lake
B. Data mart
C. Data warehouse
D. Operational database
Correct Answer: B
