WGU C207 DATA-DRIVEN DECISION-MAKING FINAL EXAM
2026/2027 | Latest Update | Questions & Verified Answers
100% Correct | Already Grade A | Pass Guaranteed - A+
Graded
Section 1: Analytics Types & Business Intelligence (Questions 1-10)
Q1. A retail company analyzes last quarter's sales data to identify which products had
the highest revenue. This is an example of:
A. Predictive analytics
B. Prescriptive analytics
C. Descriptive analytics [CORRECT]
D. Diagnostic analytics
Rationale: Descriptive analytics answers "what happened?" by summarizing historical
data. Predictive analytics (A) forecasts future outcomes. Prescriptive analytics (B)
recommends actions. Diagnostic analytics (D) explains why something happened. The
WGU C207 curriculum establishes descriptive analytics as the foundational analytics
type that provides baseline understanding before advancing to more complex analyses.
Correct Answer: C
Q2. A logistics company uses optimization algorithms to determine the most efficient
delivery routes based on traffic patterns, fuel costs, and delivery time windows. This
represents:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics [CORRECT]
,Rationale: Prescriptive analytics answers "what should we do?" by using optimization
and simulation to recommend specific actions. Route optimization with constraints is a
classic prescriptive application. Descriptive (A) and diagnostic (B) look backward.
Predictive (C) forecasts but does not recommend. The WGU C207 curriculum positions
prescriptive analytics as the most advanced type, directly supporting decision-making.
Correct Answer: D
Q3. A hospital dashboard displays real-time patient admission rates, average length of
stay, and readmission percentages. These metrics are best classified as:
A. Raw data elements
B. Key Performance Indicators (KPIs) [CORRECT]
C. Data lake repositories
D. ETL processes
Rationale: KPIs are measurable values that demonstrate effectiveness in achieving key
business objectives. Admission rates, length of stay, and readmission rates are
healthcare-specific KPIs. Raw data (A) is unprocessed. Data lakes (C) are storage
repositories. ETL (D) is a data integration process. The WGU C207 curriculum
emphasizes that KPIs must be actionable, measurable, and aligned with strategic goals.
Correct Answer: B
Q4. In OLAP multidimensional analysis, rotating the axes of a data cube to view data
from a different perspective is called:
A. Slicing
B. Dicing
C. Pivoting [CORRECT]
D. Roll-up
Rationale: Pivoting rotates the axes of a multidimensional cube to view data from
different perspectives (e.g., swapping rows and columns). Slicing (A) selects a subset
,of one dimension. Dicing (B) selects a subcube across multiple dimensions. Roll-up (D)
aggregates data to a higher level. The WGU C207 curriculum uses these OLAP
operations as fundamental business intelligence concepts.
Correct Answer: C
Q5. A data mart differs from a data warehouse in that it:
A. Contains raw, unprocessed data from all organizational sources
B. Is a subset focused on a specific department or business function [CORRECT]
C. Requires no ETL process before loading data
D. Only stores unstructured data like images and videos
Rationale: A data mart is a subject-oriented subset of a data warehouse designed for a
specific department (e.g., sales, marketing, finance). Data warehouses (A) are
enterprise-wide. Both require ETL (C). Data marts store structured data (D). The WGU
C207 curriculum distinguishes these by scope: warehouse = enterprise, mart =
department.
Correct Answer: B
Q6. A company stores social media posts, customer emails, and sensor data in their
original formats without predefined schemas. This storage repository is best described
as:
A. Data warehouse
B. Data mart
C. Data lake [CORRECT]
D. Relational database
Rationale: A data lake stores raw data in native formats (structured, semi-structured,
unstructured) without predefined schemas, enabling flexible future analysis. Data
warehouses (A) and marts (B) use structured, schema-on-write approaches. Relational
, databases (D) require predefined schemas. The WGU C207 curriculum positions data
lakes as essential for big data and machine learning applications.
Correct Answer: C
Q7. The ETL process in business intelligence stands for:
A. Evaluate, Test, Launch
B. Extract, Transform, Load [CORRECT]
C. Enter, Tabulate, List
D. Estimate, Track, Log
Rationale: ETL (Extract, Transform, Load) is the standard data integration process:
extract data from source systems, transform it into consistent formats, and load it into
the data warehouse. The other options are distractors. The WGU C207 curriculum
presents ETL as the backbone of data warehousing and business intelligence
infrastructure.
Correct Answer: B
Q8. A manufacturing company investigates why production defects increased in March
by analyzing machine maintenance logs, operator training records, and raw material
quality reports. This is:
A. Descriptive analytics
B. Diagnostic analytics [CORRECT]
C. Predictive analytics
D. Prescriptive analytics
Rationale: Diagnostic analytics answers "why did it happen?" by drilling down into data
to identify root causes. Analyzing multiple data sources to explain defect increases is
diagnostic. Descriptive (A) would simply report the defect count. Predictive (C) would
forecast future defects. Prescriptive (D) would recommend solutions. The WGU C207
2026/2027 | Latest Update | Questions & Verified Answers
100% Correct | Already Grade A | Pass Guaranteed - A+
Graded
Section 1: Analytics Types & Business Intelligence (Questions 1-10)
Q1. A retail company analyzes last quarter's sales data to identify which products had
the highest revenue. This is an example of:
A. Predictive analytics
B. Prescriptive analytics
C. Descriptive analytics [CORRECT]
D. Diagnostic analytics
Rationale: Descriptive analytics answers "what happened?" by summarizing historical
data. Predictive analytics (A) forecasts future outcomes. Prescriptive analytics (B)
recommends actions. Diagnostic analytics (D) explains why something happened. The
WGU C207 curriculum establishes descriptive analytics as the foundational analytics
type that provides baseline understanding before advancing to more complex analyses.
Correct Answer: C
Q2. A logistics company uses optimization algorithms to determine the most efficient
delivery routes based on traffic patterns, fuel costs, and delivery time windows. This
represents:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics [CORRECT]
,Rationale: Prescriptive analytics answers "what should we do?" by using optimization
and simulation to recommend specific actions. Route optimization with constraints is a
classic prescriptive application. Descriptive (A) and diagnostic (B) look backward.
Predictive (C) forecasts but does not recommend. The WGU C207 curriculum positions
prescriptive analytics as the most advanced type, directly supporting decision-making.
Correct Answer: D
Q3. A hospital dashboard displays real-time patient admission rates, average length of
stay, and readmission percentages. These metrics are best classified as:
A. Raw data elements
B. Key Performance Indicators (KPIs) [CORRECT]
C. Data lake repositories
D. ETL processes
Rationale: KPIs are measurable values that demonstrate effectiveness in achieving key
business objectives. Admission rates, length of stay, and readmission rates are
healthcare-specific KPIs. Raw data (A) is unprocessed. Data lakes (C) are storage
repositories. ETL (D) is a data integration process. The WGU C207 curriculum
emphasizes that KPIs must be actionable, measurable, and aligned with strategic goals.
Correct Answer: B
Q4. In OLAP multidimensional analysis, rotating the axes of a data cube to view data
from a different perspective is called:
A. Slicing
B. Dicing
C. Pivoting [CORRECT]
D. Roll-up
Rationale: Pivoting rotates the axes of a multidimensional cube to view data from
different perspectives (e.g., swapping rows and columns). Slicing (A) selects a subset
,of one dimension. Dicing (B) selects a subcube across multiple dimensions. Roll-up (D)
aggregates data to a higher level. The WGU C207 curriculum uses these OLAP
operations as fundamental business intelligence concepts.
Correct Answer: C
Q5. A data mart differs from a data warehouse in that it:
A. Contains raw, unprocessed data from all organizational sources
B. Is a subset focused on a specific department or business function [CORRECT]
C. Requires no ETL process before loading data
D. Only stores unstructured data like images and videos
Rationale: A data mart is a subject-oriented subset of a data warehouse designed for a
specific department (e.g., sales, marketing, finance). Data warehouses (A) are
enterprise-wide. Both require ETL (C). Data marts store structured data (D). The WGU
C207 curriculum distinguishes these by scope: warehouse = enterprise, mart =
department.
Correct Answer: B
Q6. A company stores social media posts, customer emails, and sensor data in their
original formats without predefined schemas. This storage repository is best described
as:
A. Data warehouse
B. Data mart
C. Data lake [CORRECT]
D. Relational database
Rationale: A data lake stores raw data in native formats (structured, semi-structured,
unstructured) without predefined schemas, enabling flexible future analysis. Data
warehouses (A) and marts (B) use structured, schema-on-write approaches. Relational
, databases (D) require predefined schemas. The WGU C207 curriculum positions data
lakes as essential for big data and machine learning applications.
Correct Answer: C
Q7. The ETL process in business intelligence stands for:
A. Evaluate, Test, Launch
B. Extract, Transform, Load [CORRECT]
C. Enter, Tabulate, List
D. Estimate, Track, Log
Rationale: ETL (Extract, Transform, Load) is the standard data integration process:
extract data from source systems, transform it into consistent formats, and load it into
the data warehouse. The other options are distractors. The WGU C207 curriculum
presents ETL as the backbone of data warehousing and business intelligence
infrastructure.
Correct Answer: B
Q8. A manufacturing company investigates why production defects increased in March
by analyzing machine maintenance logs, operator training records, and raw material
quality reports. This is:
A. Descriptive analytics
B. Diagnostic analytics [CORRECT]
C. Predictive analytics
D. Prescriptive analytics
Rationale: Diagnostic analytics answers "why did it happen?" by drilling down into data
to identify root causes. Analyzing multiple data sources to explain defect increases is
diagnostic. Descriptive (A) would simply report the defect count. Predictive (C) would
forecast future defects. Prescriptive (D) would recommend solutions. The WGU C207
