MGT 6203 Data Analytics for Management
Midterm Exam, 2026/2027 – 75-Question
Business Analytics Examination with Verified
Rationales
Section A: Foundations of Data Analytics & CRISP-DM (Q1–15)
1. Which of the following best describes the primary goal of data analytics in
business?
A) To collect and store large volumes of raw data
B) To transform raw data into actionable insights for decision making
C) To replace human decision making entirely
D) To ensure data is stored securely
Answer: B
Rationale: Data analytics involves examining, cleaning, transforming, and
modeling data to discover useful information and support business decision
making .
2. Which type of analytics answers the question "What happened?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: A
Rationale: Descriptive analytics summarizes historical data to understand
what has occurred in the past. Diagnostic answers "why," predictive answers
"what will happen," and prescriptive answers "what should we do" .
3. Which type of analytics answers the question "Why did it happen?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
,Answer: B
Rationale: Diagnostic analytics examines data to understand causal
relationships and the root causes of past events .
4. Which type of analytics answers the question "What will happen?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: C
Rationale: Predictive analytics uses statistical models and machine learning
to forecast future outcomes based on historical data .
5. Which type of analytics answers the question "What should we do about
it?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: D
Rationale: Prescriptive analytics goes beyond prediction to recommend
specific actions to achieve desired outcomes, often using optimization and
simulation techniques .
6. Which of the following is an example of descriptive analytics?
A) A sales dashboard showing last month's revenue by region
B) A model predicting customer churn next quarter
C) A recommendation engine suggesting products to customers
D) An optimization model for inventory levels
Answer: A
Rationale: A sales dashboard showing historical data is descriptive analytics.
Predictive models, recommendation engines, and optimization models
represent predictive or prescriptive analytics .
7. Which of the following is an example of predictive analytics?
A) A report showing total sales for the past year
B) A forecast of next month's sales based on historical trends
C) A simulation to determine optimal pricing
D) A dashboard of current inventory levels
, Answer: B
Rationale: Forecasting future sales based on historical trends is predictive
analytics. Descriptive analytics focuses on past data; prescriptive on
optimization .
8. The CRISP-DM framework stands for:
A) Cross-Industry Standard Process for Data Mining
B) Cross-Industry Systematic Process for Data Management
C) Comprehensive Research and Integrated System for Data Mining
D) Cross-Reference Integrated System for Data Mining
Answer: A
Rationale: CRISP-DM is a widely used framework for data mining and
analytics projects, consisting of six phases: business understanding, data
understanding, data preparation, modeling, evaluation, and deployment .
9. In the CRISP-DM framework, what is the correct order of the first three
phases?
A) Data Preparation, Business Understanding, Modeling
B) Business Understanding, Data Understanding, Data Preparation
C) Modeling, Evaluation, Deployment
D) Data Collection, Analysis, Reporting
Answer: B
Rationale: CRISP-DM begins with Business Understanding, then Data
Understanding, then Data Preparation—establishing business objectives
before technical work .
10. Which of the following is NOT a phase in the CRISP-DM framework?
A) Business understanding
B) Data understanding
C) Data deployment
D) Modeling
Answer: C
Rationale: The six phases are business understanding, data understanding,
data preparation, modeling, evaluation, and deployment. "Data deployment"
is not a standard phase .
11. The phase in which data is cleaned, transformed, and formatted for
analysis is called:
A) Data understanding
B) Data preparation
Midterm Exam, 2026/2027 – 75-Question
Business Analytics Examination with Verified
Rationales
Section A: Foundations of Data Analytics & CRISP-DM (Q1–15)
1. Which of the following best describes the primary goal of data analytics in
business?
A) To collect and store large volumes of raw data
B) To transform raw data into actionable insights for decision making
C) To replace human decision making entirely
D) To ensure data is stored securely
Answer: B
Rationale: Data analytics involves examining, cleaning, transforming, and
modeling data to discover useful information and support business decision
making .
2. Which type of analytics answers the question "What happened?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: A
Rationale: Descriptive analytics summarizes historical data to understand
what has occurred in the past. Diagnostic answers "why," predictive answers
"what will happen," and prescriptive answers "what should we do" .
3. Which type of analytics answers the question "Why did it happen?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
,Answer: B
Rationale: Diagnostic analytics examines data to understand causal
relationships and the root causes of past events .
4. Which type of analytics answers the question "What will happen?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: C
Rationale: Predictive analytics uses statistical models and machine learning
to forecast future outcomes based on historical data .
5. Which type of analytics answers the question "What should we do about
it?"
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
Answer: D
Rationale: Prescriptive analytics goes beyond prediction to recommend
specific actions to achieve desired outcomes, often using optimization and
simulation techniques .
6. Which of the following is an example of descriptive analytics?
A) A sales dashboard showing last month's revenue by region
B) A model predicting customer churn next quarter
C) A recommendation engine suggesting products to customers
D) An optimization model for inventory levels
Answer: A
Rationale: A sales dashboard showing historical data is descriptive analytics.
Predictive models, recommendation engines, and optimization models
represent predictive or prescriptive analytics .
7. Which of the following is an example of predictive analytics?
A) A report showing total sales for the past year
B) A forecast of next month's sales based on historical trends
C) A simulation to determine optimal pricing
D) A dashboard of current inventory levels
, Answer: B
Rationale: Forecasting future sales based on historical trends is predictive
analytics. Descriptive analytics focuses on past data; prescriptive on
optimization .
8. The CRISP-DM framework stands for:
A) Cross-Industry Standard Process for Data Mining
B) Cross-Industry Systematic Process for Data Management
C) Comprehensive Research and Integrated System for Data Mining
D) Cross-Reference Integrated System for Data Mining
Answer: A
Rationale: CRISP-DM is a widely used framework for data mining and
analytics projects, consisting of six phases: business understanding, data
understanding, data preparation, modeling, evaluation, and deployment .
9. In the CRISP-DM framework, what is the correct order of the first three
phases?
A) Data Preparation, Business Understanding, Modeling
B) Business Understanding, Data Understanding, Data Preparation
C) Modeling, Evaluation, Deployment
D) Data Collection, Analysis, Reporting
Answer: B
Rationale: CRISP-DM begins with Business Understanding, then Data
Understanding, then Data Preparation—establishing business objectives
before technical work .
10. Which of the following is NOT a phase in the CRISP-DM framework?
A) Business understanding
B) Data understanding
C) Data deployment
D) Modeling
Answer: C
Rationale: The six phases are business understanding, data understanding,
data preparation, modeling, evaluation, and deployment. "Data deployment"
is not a standard phase .
11. The phase in which data is cleaned, transformed, and formatted for
analysis is called:
A) Data understanding
B) Data preparation
