WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: What happens in the Data Mining Phase?
Answer:
Creating training and testing datasets to build models from Identify/detect patterns
Determine if groups (clusters) exist in data Classify data into groups Create models
that "learn" and improve (e.g., machine/deep learning, AI, etc) Test Hypotheses
Refine
Q: Another name for Reporting and Visualization
Answer:
Dashboards
Q: What happens in the Reporting/Visualization phase?
Answer:
Tell a story with data Provide a summary of analytic analysis Provide insights to
stakeholders Create insightful graphs that showcase trends and forecasts
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential Problems with Data Cleaning
Answer:
Some cleaning techniques could dramatically change
data/outcomes
Outliers not dealt with can cause problems with statistical models due to excessive
variability.
Q: Potential Problems with Business Understanding
Answer:
Lack of clear focus on stakeholders,
timeline, limitations and budget could potentially derail an analysis
Q: Potential Problems with Data Acquisition
Answer:
Quality and type of data may make access more
difficult
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential problems with Data Exploration
Answer:
Skipping these steps could enable faulty
perceptions of the data which hurt advanced analytics
Q: Potential problems with Predictive Modeling
Answer:
Too many input variables (predictors) can
cause problems
Correlation does not imply causation
Time series models often need sufficient time data to offer precise trending
Predictive model accuracy should be assessed using cross-validation.
Q: Potential problems with Data Mining
Answer:
Running an entire data is problematic; need to subset
data into training and testing datasets to build models
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential problem with Report/Visualization
Answer:
Due to potential large audience consumption,
mistakes can cause bad business decisions and loss of revenue
Improper scales used in graphs could push for interpretations of the story that is
inaccurate
Q: Causation
Answer:
is when there is a real-world explanation for WHY this is logically happening; it
implies a cause and effect
Q: C, and C++, and Java
Answer:
are general-purpose languages that are used for the back end, the
foundational elementsterm-26 of data science, and they provide maximum speed
Answers with Verified Solutions | Latest 2026 Update
Q: What happens in the Data Mining Phase?
Answer:
Creating training and testing datasets to build models from Identify/detect patterns
Determine if groups (clusters) exist in data Classify data into groups Create models
that "learn" and improve (e.g., machine/deep learning, AI, etc) Test Hypotheses
Refine
Q: Another name for Reporting and Visualization
Answer:
Dashboards
Q: What happens in the Reporting/Visualization phase?
Answer:
Tell a story with data Provide a summary of analytic analysis Provide insights to
stakeholders Create insightful graphs that showcase trends and forecasts
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential Problems with Data Cleaning
Answer:
Some cleaning techniques could dramatically change
data/outcomes
Outliers not dealt with can cause problems with statistical models due to excessive
variability.
Q: Potential Problems with Business Understanding
Answer:
Lack of clear focus on stakeholders,
timeline, limitations and budget could potentially derail an analysis
Q: Potential Problems with Data Acquisition
Answer:
Quality and type of data may make access more
difficult
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential problems with Data Exploration
Answer:
Skipping these steps could enable faulty
perceptions of the data which hurt advanced analytics
Q: Potential problems with Predictive Modeling
Answer:
Too many input variables (predictors) can
cause problems
Correlation does not imply causation
Time series models often need sufficient time data to offer precise trending
Predictive model accuracy should be assessed using cross-validation.
Q: Potential problems with Data Mining
Answer:
Running an entire data is problematic; need to subset
data into training and testing datasets to build models
, WGU D204 Data Analytics Journey Terminology Questions and
Answers with Verified Solutions | Latest 2026 Update
Q: Potential problem with Report/Visualization
Answer:
Due to potential large audience consumption,
mistakes can cause bad business decisions and loss of revenue
Improper scales used in graphs could push for interpretations of the story that is
inaccurate
Q: Causation
Answer:
is when there is a real-world explanation for WHY this is logically happening; it
implies a cause and effect
Q: C, and C++, and Java
Answer:
are general-purpose languages that are used for the back end, the
foundational elementsterm-26 of data science, and they provide maximum speed
