D204 WGU Study Set 2023/ 91 Complete
Questions & Answers.
Which of these is NOT a topic of interest for Discovery/Planning/Business
Understanding?
A. Project Scope
B. Identify stakeholders and research questions/KPIs
C. Build a data pipeline (ETL)
D. Identify timeline, budget, and participants - -C
-What is a potential problem to consider in the planning phase?
A. Lack of clear focus on stakeholders, timeline, limitations, and budget
B. Quality and type of data may make access more difficult
C. Some cleaning techniques could dramatically change data/outcomes
D. Outliers not dealt with can cause problems with statistical models due to excessive
variability. - -A
-In what phase does the analyst identify the stake holders and research questions? - -
Business Understanding/Planning/Discovery
-In what phase does the analyst deal with the following:
Gather/collect data from a variety of sources
Provide structure to data accessible via relational databases (SQL)
Build data pipeline (ETL)
Use of API to download data from an external source - -Data acquisition
-In what phase does the analyst deal with the following:
Fixing improperly formatted values
Dealing with duplicates, missing data, and outliers
Data reduction - -Data cleaning/wrangling/scrubbing/munging
-In what phase does the analyst deal with the following:
Central Tendency/ Measures of center (e.g., mean, median, mode), variability (e.g.,
standard deviations and quartiles) and distributions (e.g., normal, skewed, etc)
Identify basic correlations between variables
Pattern discovery - -Data exploration/Exploratory Data Analysis(EDA)/Descriptive
Statistics
-In what phase does the analyst deal with the following:
Estimate/project future values or likelihood of an event.
Extend correlations found in EDA to mathematical models
Predict/determine output values based on input values
Cross-validation of predictive models to ensure accuracy. - -Predictive Modeling/Data
Modeling/Correlation based models/Regression models/Time Series
, -In what phase does the analyst deal with the following:
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) - -Data
Mining/Machine Learning/AI/Supervised, Unsupervised Models
-In what phase does the analyst deal with the following:
Tell a story with data
Provide a summary of analytic analysis
Provide insights to stakeholders
Create insightful graphs that showcase trends and forecasts - -Reporting and
visualization/Dashboards
-What is a potential problem in the data acquisition/query/collection step? - -Quality
and type of data may make access more difficult
-What are two potential problems in the Data Cleaning/Wrangling step? - -Some
cleaning techniques could dramatically change data/outcomes
Outliers not dealt with can cause problems with statistical models due to excessive
variability.
-What is a potential problem in the data exploration/descriptive statistics step? - -
Skipping this step could enable faulty perceptions of the data which hurt advanced
analytics.
-What are potential problems in the Predictive Modeling step? - -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.
-What is a potential problem in the data mining/supervised models step? - -Running
on entire data is problematic; need to subset data into training and testing datasets to
build models.
-What are two potential problems in the reporting and visualization/dashboards step? -
-Due to potential large audience consumption, mistakes can cause bad business
decisions and loss of revenue
Questions & Answers.
Which of these is NOT a topic of interest for Discovery/Planning/Business
Understanding?
A. Project Scope
B. Identify stakeholders and research questions/KPIs
C. Build a data pipeline (ETL)
D. Identify timeline, budget, and participants - -C
-What is a potential problem to consider in the planning phase?
A. Lack of clear focus on stakeholders, timeline, limitations, and budget
B. Quality and type of data may make access more difficult
C. Some cleaning techniques could dramatically change data/outcomes
D. Outliers not dealt with can cause problems with statistical models due to excessive
variability. - -A
-In what phase does the analyst identify the stake holders and research questions? - -
Business Understanding/Planning/Discovery
-In what phase does the analyst deal with the following:
Gather/collect data from a variety of sources
Provide structure to data accessible via relational databases (SQL)
Build data pipeline (ETL)
Use of API to download data from an external source - -Data acquisition
-In what phase does the analyst deal with the following:
Fixing improperly formatted values
Dealing with duplicates, missing data, and outliers
Data reduction - -Data cleaning/wrangling/scrubbing/munging
-In what phase does the analyst deal with the following:
Central Tendency/ Measures of center (e.g., mean, median, mode), variability (e.g.,
standard deviations and quartiles) and distributions (e.g., normal, skewed, etc)
Identify basic correlations between variables
Pattern discovery - -Data exploration/Exploratory Data Analysis(EDA)/Descriptive
Statistics
-In what phase does the analyst deal with the following:
Estimate/project future values or likelihood of an event.
Extend correlations found in EDA to mathematical models
Predict/determine output values based on input values
Cross-validation of predictive models to ensure accuracy. - -Predictive Modeling/Data
Modeling/Correlation based models/Regression models/Time Series
, -In what phase does the analyst deal with the following:
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) - -Data
Mining/Machine Learning/AI/Supervised, Unsupervised Models
-In what phase does the analyst deal with the following:
Tell a story with data
Provide a summary of analytic analysis
Provide insights to stakeholders
Create insightful graphs that showcase trends and forecasts - -Reporting and
visualization/Dashboards
-What is a potential problem in the data acquisition/query/collection step? - -Quality
and type of data may make access more difficult
-What are two potential problems in the Data Cleaning/Wrangling step? - -Some
cleaning techniques could dramatically change data/outcomes
Outliers not dealt with can cause problems with statistical models due to excessive
variability.
-What is a potential problem in the data exploration/descriptive statistics step? - -
Skipping this step could enable faulty perceptions of the data which hurt advanced
analytics.
-What are potential problems in the Predictive Modeling step? - -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.
-What is a potential problem in the data mining/supervised models step? - -Running
on entire data is problematic; need to subset data into training and testing datasets to
build models.
-What are two potential problems in the reporting and visualization/dashboards step? -
-Due to potential large audience consumption, mistakes can cause bad business
decisions and loss of revenue
