WGU D491 Introduction to Analytics
FINAL EXAM QUESTIONS WITH
CORRECT DETAILED
SOLUTIONS||100% GUARANTEED
PASS||ALREADY A+
GRADED||UPDATED 2026D/2027
SYLLABUS||<<NEWEST VERSION>>
STATISTICA - ANSWER ✓ Well-regarded tool for data mining and analytics.
Mathematica - ANSWER ✓ Popular software for advanced data analysis and
computation.
R - ANSWER ✓ Procedural language for statistical computing and graphics.
PL/R - ANSWER ✓ Integrates R commands within PostgreSQL database.
Octave - ANSWER ✓ Free alternative to Matlab for computational modeling.
WEKA - ANSWER ✓ Free data mining software with an analytical workbench.
Python - ANSWER ✓ Programming language with machine learning toolkits.
SQL - ANSWER ✓ Language for managing and querying relational databases.
Data engineer - ANSWER ✓ Stakeholder who extracts and transforms data during
the discovery phase
Data analysis, system integration, and training - ANSWER ✓ Skills crucial for
project team members working on CRM system implementation
, Initial hypothesis - ANSWER ✓ Integral part of the discovery phase that guides
subsequent data activities
Anyone who will benefit from the project - ANSWER ✓ Stakeholders included in
an analytics project
Data scientists - ANSWER ✓ Stakeholder group that offers suggestions on ideas
to test during the discovery phase
Collection of data - ANSWER ✓ Activity during the data preparation phase of the
data analytics lifecycle
Line charts - ANSWER ✓ Data visualization most suitable for understanding the
trend and progression of a variable over time
Conducting data profiling - ANSWER ✓ Task commonly performed to identify
and address data quality issues during the data preparation phase
Imputation - ANSWER ✓ Common data cleaning task used to address missing
data in a dataset
Truncating extreme values - ANSWER ✓ Task typically performed to handle
outliers during the data preparation phase
Exploring available data to understand its characteristics and suitability -
ANSWER ✓ Activity performed by a data analyst during the data preparation
phase
Model planning - ANSWER ✓ Phase of a data analysis project that involves
selecting relevant features for modeling
R - ANSWER ✓ Programming language primarily used for statistical analysis and
data manipulation in the model planning phase
Naive Bayes - ANSWER ✓ Classification model based on probability used to
assign class labels
, SAS Enterprise Miner - ANSWER ✓ Tool used to connect users to relational
databases and data warehouse appliances in the model planning phase
Linear regression - ANSWER ✓ Regression model commonly used for predicting
a continuous numerical outcome
Model execution phase - ANSWER ✓ Phase of the data analytics lifecycle that
involves running analytical software packages on small datasets
Result analysis - ANSWER ✓ Step typically performed after executing the model
in the model execution phase
Cross-validation - ANSWER ✓ Testing procedure used for evaluating the
performance of a model
Applying the trained model to new data for predictions - ANSWER ✓ Role of the
SPSS modeler in the model execution phase
Implementing data-driven insights into business functions - ANSWER ✓ Purpose
of communicating data analytics results to stakeholders
By implementing personalized outreach to customers - ANSWER ✓ How
communication of results ties to the operationalize phase of data analytics
Communicate results - ANSWER ✓ Immediate predecessor to the operationalize
phase of the data analytics life cycle
Implementing and maintaining the analytics solution in a production environment
- ANSWER ✓ Primary objective of the operationalize phase in the data analytics
life cycle
To make sure their reports and dashboards are up-to-date - ANSWER ✓ Primary
responsibility of the business intelligence analyst during the operationalize phase
What factors are associated with patient satisfaction? - ANSWER ✓ Question to
be answered by analyzing patient feedback data
FINAL EXAM QUESTIONS WITH
CORRECT DETAILED
SOLUTIONS||100% GUARANTEED
PASS||ALREADY A+
GRADED||UPDATED 2026D/2027
SYLLABUS||<<NEWEST VERSION>>
STATISTICA - ANSWER ✓ Well-regarded tool for data mining and analytics.
Mathematica - ANSWER ✓ Popular software for advanced data analysis and
computation.
R - ANSWER ✓ Procedural language for statistical computing and graphics.
PL/R - ANSWER ✓ Integrates R commands within PostgreSQL database.
Octave - ANSWER ✓ Free alternative to Matlab for computational modeling.
WEKA - ANSWER ✓ Free data mining software with an analytical workbench.
Python - ANSWER ✓ Programming language with machine learning toolkits.
SQL - ANSWER ✓ Language for managing and querying relational databases.
Data engineer - ANSWER ✓ Stakeholder who extracts and transforms data during
the discovery phase
Data analysis, system integration, and training - ANSWER ✓ Skills crucial for
project team members working on CRM system implementation
, Initial hypothesis - ANSWER ✓ Integral part of the discovery phase that guides
subsequent data activities
Anyone who will benefit from the project - ANSWER ✓ Stakeholders included in
an analytics project
Data scientists - ANSWER ✓ Stakeholder group that offers suggestions on ideas
to test during the discovery phase
Collection of data - ANSWER ✓ Activity during the data preparation phase of the
data analytics lifecycle
Line charts - ANSWER ✓ Data visualization most suitable for understanding the
trend and progression of a variable over time
Conducting data profiling - ANSWER ✓ Task commonly performed to identify
and address data quality issues during the data preparation phase
Imputation - ANSWER ✓ Common data cleaning task used to address missing
data in a dataset
Truncating extreme values - ANSWER ✓ Task typically performed to handle
outliers during the data preparation phase
Exploring available data to understand its characteristics and suitability -
ANSWER ✓ Activity performed by a data analyst during the data preparation
phase
Model planning - ANSWER ✓ Phase of a data analysis project that involves
selecting relevant features for modeling
R - ANSWER ✓ Programming language primarily used for statistical analysis and
data manipulation in the model planning phase
Naive Bayes - ANSWER ✓ Classification model based on probability used to
assign class labels
, SAS Enterprise Miner - ANSWER ✓ Tool used to connect users to relational
databases and data warehouse appliances in the model planning phase
Linear regression - ANSWER ✓ Regression model commonly used for predicting
a continuous numerical outcome
Model execution phase - ANSWER ✓ Phase of the data analytics lifecycle that
involves running analytical software packages on small datasets
Result analysis - ANSWER ✓ Step typically performed after executing the model
in the model execution phase
Cross-validation - ANSWER ✓ Testing procedure used for evaluating the
performance of a model
Applying the trained model to new data for predictions - ANSWER ✓ Role of the
SPSS modeler in the model execution phase
Implementing data-driven insights into business functions - ANSWER ✓ Purpose
of communicating data analytics results to stakeholders
By implementing personalized outreach to customers - ANSWER ✓ How
communication of results ties to the operationalize phase of data analytics
Communicate results - ANSWER ✓ Immediate predecessor to the operationalize
phase of the data analytics life cycle
Implementing and maintaining the analytics solution in a production environment
- ANSWER ✓ Primary objective of the operationalize phase in the data analytics
life cycle
To make sure their reports and dashboards are up-to-date - ANSWER ✓ Primary
responsibility of the business intelligence analyst during the operationalize phase
What factors are associated with patient satisfaction? - ANSWER ✓ Question to
be answered by analyzing patient feedback data
