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WGU D204 Data Analytics OA Exam – Latest
Version A with Complete 300 Questions and
Verified Answers Released
Official Exam Overview:
The WGU D204 Data Analytics OA Exam evaluates learners’ understanding of the full data
analytics lifecycle, including data collection, cleaning, exploration, modeling, and interpretation.
The exam emphasizes analytical reasoning, research methods, and application of statistical and
computational techniques to real-world problems.
Exam Coverage Areas:
• Phases of the Data Analytics Process
• Data Collection, Cleaning, and Transformation
• Exploratory Analysis and Data Visualization
• Statistical Modeling and Predictive Techniques
• Data Mining and Pattern Discovery
• Machine Learning Fundamentals for Analytics
• Ethical, Privacy, and Governance Considerations
• Tools, Software, and Reporting Practices
• Interpretation and Presentation of Analytical Findings
Question Formats: Multiple choice, scenario-based
QUESTION 1: A data analyst notices that the dataset has been greatly reduced, leaving sample
sizes too small for reliable conclusions. At which phase of the data analytics lifecycle did this
most likely occur?
a) Data exploration
b) Data modeling
c) Data mining ✅
d) Data discovery
Rationale: Sample size reduction affecting dataset reliability typically occurs during data
mining, when patterns are extracted and datasets are refined.
QUESTION 2: During which stage are raw data cleaned, transformed, and prepped for analysis?
,a) Data modeling
b) Data preparation ✅
c) Data visualization
d) Data discovery
Rationale: Data preparation ensures accuracy, completeness, and proper formatting of raw data
before further analysis.
QUESTION 3: Which process is primarily used to detect trends, relationships, or patterns in
large datasets?
a) Regression analysis
b) Data mining ✅
c) Hypothesis testing
d) Descriptive statistics
Rationale: Data mining uses computational and statistical methods to uncover patterns,
correlations, and insights from complex datasets.
QUESTION 4: The main objective of predictive analytics is to:
a) Describe past trends
b) Identify variable correlations
c) Forecast future outcomes based on historical data ✅
d) Create visual charts and graphs
Rationale: Predictive analytics applies models to historical data to anticipate future events or
behaviors, aiding in informed decision-making.
QUESTION 5: Ethical practices in data analytics primarily focus on:
a) Faster data processing
b) Ensuring biased results
c) Maintaining privacy, fairness, and accuracy ✅
d) Automatically generating models
Rationale: Ethical standards ensure data integrity, protect privacy, and prevent biased or unfair
use of analytics.
An analyst realizes that the data set has been reduced significantly, resulting in sample sizes
that are too small. In which phase of the data analytics life cycle did this likely occur?
a. Data exploration
b. Data modeling
c. Data mining
,d. Data discovery
c. Data mining
What strategy will contribute to effective data representation and reporting?
a.Creating a new training data set
b.Selecting data for a prediction model
c.Excluding unrelated data
d.Extracting data from source repositories
c.Excluding unrelated data
What are two purposes of the reporting phase of the data analytics life cycle? Select two
answers:
a. Provide the conclusions from the analysis in an engaging manner
b. Provide a tool for decision-makers to import and analyze more data
c. Provide actionable insights that can inform decision-making
d. Provide an automated way for decision-makers to test their own models
a. Provide the conclusions from the analysis in an engaging manner
c.Provide actionable insights that can inform decision-making
A data analyst identified combinations of sales that frequently occur together in data over
the past 5 years. Which phase of the data analytics life cycle is represented by this analysis?
a.Data acquisition
b. Representation and reporting
c.Data mining
d.Predictive modeling
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, Page 2 of 45
c. Data mining
During which phase of the data analytics life cycle does an analyst create a story to report
data?
a. Data acquisition
b. Data mining
c. Data reporting
d. Data cleaning
c.Data reporting
What is a characteristic of active listening?
a. Active working on a task while listening to the speaker
b. Seeking to understand the speaker's emotions and intent
c. Focusing intently on the content of the message
d. Waiting patiently to share one's own thoughts
b.Seeking to understand the speaker's emotions and intent
What will be a consequence of poor attention to detail during the data exploration phase?
a. Not enough variables will be considered in the analysis.
b. The outcome of the analysis will be misaligned to business needs.
c. The analyst will lack insight into the structure of the data set.
d. The model will be built using the wrong data set.
c.The analyst will lack insight into the structure of the data set.
Data visualization can be considered an example of what?
a.data science without big data
b. Data science with big data
c. Both A and B
d. None of the above
a.data science without big data
What questions will data analytics consider improving 10% market share value to open new
store in a different location?
a. Get list of geographic areas
b. Reduce staff pay by 10%
c. Check compatible market value
d. None of the above
C Check compatible market value
2
WGU D204 Data Analytics OA Exam – Latest
Version A with Complete 300 Questions and
Verified Answers Released
Official Exam Overview:
The WGU D204 Data Analytics OA Exam evaluates learners’ understanding of the full data
analytics lifecycle, including data collection, cleaning, exploration, modeling, and interpretation.
The exam emphasizes analytical reasoning, research methods, and application of statistical and
computational techniques to real-world problems.
Exam Coverage Areas:
• Phases of the Data Analytics Process
• Data Collection, Cleaning, and Transformation
• Exploratory Analysis and Data Visualization
• Statistical Modeling and Predictive Techniques
• Data Mining and Pattern Discovery
• Machine Learning Fundamentals for Analytics
• Ethical, Privacy, and Governance Considerations
• Tools, Software, and Reporting Practices
• Interpretation and Presentation of Analytical Findings
Question Formats: Multiple choice, scenario-based
QUESTION 1: A data analyst notices that the dataset has been greatly reduced, leaving sample
sizes too small for reliable conclusions. At which phase of the data analytics lifecycle did this
most likely occur?
a) Data exploration
b) Data modeling
c) Data mining ✅
d) Data discovery
Rationale: Sample size reduction affecting dataset reliability typically occurs during data
mining, when patterns are extracted and datasets are refined.
QUESTION 2: During which stage are raw data cleaned, transformed, and prepped for analysis?
,a) Data modeling
b) Data preparation ✅
c) Data visualization
d) Data discovery
Rationale: Data preparation ensures accuracy, completeness, and proper formatting of raw data
before further analysis.
QUESTION 3: Which process is primarily used to detect trends, relationships, or patterns in
large datasets?
a) Regression analysis
b) Data mining ✅
c) Hypothesis testing
d) Descriptive statistics
Rationale: Data mining uses computational and statistical methods to uncover patterns,
correlations, and insights from complex datasets.
QUESTION 4: The main objective of predictive analytics is to:
a) Describe past trends
b) Identify variable correlations
c) Forecast future outcomes based on historical data ✅
d) Create visual charts and graphs
Rationale: Predictive analytics applies models to historical data to anticipate future events or
behaviors, aiding in informed decision-making.
QUESTION 5: Ethical practices in data analytics primarily focus on:
a) Faster data processing
b) Ensuring biased results
c) Maintaining privacy, fairness, and accuracy ✅
d) Automatically generating models
Rationale: Ethical standards ensure data integrity, protect privacy, and prevent biased or unfair
use of analytics.
An analyst realizes that the data set has been reduced significantly, resulting in sample sizes
that are too small. In which phase of the data analytics life cycle did this likely occur?
a. Data exploration
b. Data modeling
c. Data mining
,d. Data discovery
c. Data mining
What strategy will contribute to effective data representation and reporting?
a.Creating a new training data set
b.Selecting data for a prediction model
c.Excluding unrelated data
d.Extracting data from source repositories
c.Excluding unrelated data
What are two purposes of the reporting phase of the data analytics life cycle? Select two
answers:
a. Provide the conclusions from the analysis in an engaging manner
b. Provide a tool for decision-makers to import and analyze more data
c. Provide actionable insights that can inform decision-making
d. Provide an automated way for decision-makers to test their own models
a. Provide the conclusions from the analysis in an engaging manner
c.Provide actionable insights that can inform decision-making
A data analyst identified combinations of sales that frequently occur together in data over
the past 5 years. Which phase of the data analytics life cycle is represented by this analysis?
a.Data acquisition
b. Representation and reporting
c.Data mining
d.Predictive modeling
1
, Page 2 of 45
c. Data mining
During which phase of the data analytics life cycle does an analyst create a story to report
data?
a. Data acquisition
b. Data mining
c. Data reporting
d. Data cleaning
c.Data reporting
What is a characteristic of active listening?
a. Active working on a task while listening to the speaker
b. Seeking to understand the speaker's emotions and intent
c. Focusing intently on the content of the message
d. Waiting patiently to share one's own thoughts
b.Seeking to understand the speaker's emotions and intent
What will be a consequence of poor attention to detail during the data exploration phase?
a. Not enough variables will be considered in the analysis.
b. The outcome of the analysis will be misaligned to business needs.
c. The analyst will lack insight into the structure of the data set.
d. The model will be built using the wrong data set.
c.The analyst will lack insight into the structure of the data set.
Data visualization can be considered an example of what?
a.data science without big data
b. Data science with big data
c. Both A and B
d. None of the above
a.data science without big data
What questions will data analytics consider improving 10% market share value to open new
store in a different location?
a. Get list of geographic areas
b. Reduce staff pay by 10%
c. Check compatible market value
d. None of the above
C Check compatible market value
2
