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D204 WGU Exam Study Guide 100% Correct Verified 2024 Version

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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 valuesDealing 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

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D204 WGU Exam Study Guide | 100%
Correct | Verified | 2024 Version
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

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