WGU C207 DATA-DRIVEN DECISION MAKING VOCABULARY
2026/2027 | Verified Definitions 100% Correct | Complete
Glossary Guide | Pass Guaranteed - A+ Graded
Part 1: Foundations of Data-Driven Decision Making & Analytics Types
This section establishes the core vocabulary for understanding how organizations use
data to make informed decisions. These terms form the foundation of business analytics.
Q1: Which term describes the process of using data to guide business decisions and
strategy?
A. Data warehousing for storage optimization
B. Data-driven decision making (DDDM) [CORRECT]
C. Data visualization for presentation
D. Data mining for pattern discovery
Correct Answer: B
Rationale: Data-driven decision making (DDDM) is the practice of basing decisions on
data analysis rather than intuition or observation alone. It involves collecting data,
analyzing it for insights, and using those insights to guide actions. While warehousing,
visualization, and mining are components, DDDM encompasses the entire
decision-making philosophy.
,Q2: What type of analytics answers the question "what happened?" by summarizing
historical data?
A. Predictive analytics
B. Prescriptive analytics
C. Descriptive analytics [CORRECT]
D. Cognitive analytics
Correct Answer: C
Rationale: Descriptive analytics is the foundation of business intelligence that examines
historical data to describe what occurred. It uses techniques like data aggregation,
dashboards, and reports to provide visibility into past performance. Predictive analytics
forecasts future events; prescriptive analytics recommends actions; cognitive analytics
uses AI for insights.
Q3: Which analytics type focuses on "why did it happen?" through root cause analysis?
A. Descriptive analytics
B. Diagnostic analytics [CORRECT]
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: B
Rationale: Diagnostic analytics examines data to understand causes and determine why
something happened. It uses techniques like drill-down, data discovery, and correlations
,to identify root causes. This bridges descriptive (what happened) and predictive (what
will happen) analytics.
Q4: What type of analytics uses statistical models and machine learning to answer
"what will happen?"
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics [CORRECT]
D. Cognitive analytics
Correct Answer: C
Rationale: Predictive analytics uses historical data, statistical algorithms, and machine
learning to identify the likelihood of future outcomes. It includes regression,
classification, time series forecasting, and neural networks. This differs from
prescriptive analytics (what should we do) and descriptive analytics (what happened).
Q5: Which advanced analytics type answers "what should we do?" by recommending
optimal actions?
A. Predictive analytics
B. Prescriptive analytics [CORRECT]
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: B
, Rationale: Prescriptive analytics goes beyond prediction to recommend specific actions
that will achieve desired outcomes. It uses optimization, simulation, and decision
analysis to suggest the best course of action. This is the most advanced form of
analytics, often combining AI with business rules.
Q6: What is the cross-industry standard methodology for data mining projects
consisting of six phases: Business Understanding, Data Understanding, Data
Preparation, Modeling, Evaluation, and Deployment?
A. SEMMA methodology
B. KDD process
C. CRISP-DM [CORRECT]
D. OODA loop
Correct Answer: C
Rationale: CRISP-DM (Cross-Industry Standard Process for Data Mining) is the most
widely used methodology for data mining and analytics projects. Its six phases provide
a structured approach from business problem definition through deployment. SEMMA
(Sample, Explore, Modify, Model, Assess) is SAS-specific; KDD is Knowledge Discovery
in Databases; OODA is a decision-making loop.
Q7: Which term describes the process of discovering patterns, correlations, and insights
from large datasets using statistical and machine learning techniques?
A. Data warehousing
B. Data mining [CORRECT]
2026/2027 | Verified Definitions 100% Correct | Complete
Glossary Guide | Pass Guaranteed - A+ Graded
Part 1: Foundations of Data-Driven Decision Making & Analytics Types
This section establishes the core vocabulary for understanding how organizations use
data to make informed decisions. These terms form the foundation of business analytics.
Q1: Which term describes the process of using data to guide business decisions and
strategy?
A. Data warehousing for storage optimization
B. Data-driven decision making (DDDM) [CORRECT]
C. Data visualization for presentation
D. Data mining for pattern discovery
Correct Answer: B
Rationale: Data-driven decision making (DDDM) is the practice of basing decisions on
data analysis rather than intuition or observation alone. It involves collecting data,
analyzing it for insights, and using those insights to guide actions. While warehousing,
visualization, and mining are components, DDDM encompasses the entire
decision-making philosophy.
,Q2: What type of analytics answers the question "what happened?" by summarizing
historical data?
A. Predictive analytics
B. Prescriptive analytics
C. Descriptive analytics [CORRECT]
D. Cognitive analytics
Correct Answer: C
Rationale: Descriptive analytics is the foundation of business intelligence that examines
historical data to describe what occurred. It uses techniques like data aggregation,
dashboards, and reports to provide visibility into past performance. Predictive analytics
forecasts future events; prescriptive analytics recommends actions; cognitive analytics
uses AI for insights.
Q3: Which analytics type focuses on "why did it happen?" through root cause analysis?
A. Descriptive analytics
B. Diagnostic analytics [CORRECT]
C. Predictive analytics
D. Prescriptive analytics
Correct Answer: B
Rationale: Diagnostic analytics examines data to understand causes and determine why
something happened. It uses techniques like drill-down, data discovery, and correlations
,to identify root causes. This bridges descriptive (what happened) and predictive (what
will happen) analytics.
Q4: What type of analytics uses statistical models and machine learning to answer
"what will happen?"
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics [CORRECT]
D. Cognitive analytics
Correct Answer: C
Rationale: Predictive analytics uses historical data, statistical algorithms, and machine
learning to identify the likelihood of future outcomes. It includes regression,
classification, time series forecasting, and neural networks. This differs from
prescriptive analytics (what should we do) and descriptive analytics (what happened).
Q5: Which advanced analytics type answers "what should we do?" by recommending
optimal actions?
A. Predictive analytics
B. Prescriptive analytics [CORRECT]
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: B
, Rationale: Prescriptive analytics goes beyond prediction to recommend specific actions
that will achieve desired outcomes. It uses optimization, simulation, and decision
analysis to suggest the best course of action. This is the most advanced form of
analytics, often combining AI with business rules.
Q6: What is the cross-industry standard methodology for data mining projects
consisting of six phases: Business Understanding, Data Understanding, Data
Preparation, Modeling, Evaluation, and Deployment?
A. SEMMA methodology
B. KDD process
C. CRISP-DM [CORRECT]
D. OODA loop
Correct Answer: C
Rationale: CRISP-DM (Cross-Industry Standard Process for Data Mining) is the most
widely used methodology for data mining and analytics projects. Its six phases provide
a structured approach from business problem definition through deployment. SEMMA
(Sample, Explore, Modify, Model, Assess) is SAS-specific; KDD is Knowledge Discovery
in Databases; OODA is a decision-making loop.
Q7: Which term describes the process of discovering patterns, correlations, and insights
from large datasets using statistical and machine learning techniques?
A. Data warehousing
B. Data mining [CORRECT]
