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WGU D491 INTRODUTION TO ANALYTICS AND PRACTICE EXAM (TEST BANK) WITH CORRECT Qs and As FROM EXPERT What are the different types of data analytics projects? - Data warehousing, data mining, data visualization, and business intelligence - Regression ana

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WGU D491 INTRODUTION TO ANALYTICS AND PRACTICE

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WGU D491 INTRODUTION TO ANALYTICS
AND PRACTICE EXAM (TEST BANK) WITH
CORRECT Qs and As FROM EXPERT

What are the different types of data analytics projects?

- Data warehousing, data mining, data visualization, and
business intelligence
- Regression analysis, time series analysis, text analytics,
and network analysis
- Data collection, data cleaning, data transformation, and
data visualization
- Descriptive, diagnostic, predictive, and prescriptive
analytics
ANSWER-Descriptive, diagnostic, predictive, and
prescriptive analytics

What is the difference between exploratory and
confirmatory data analytics projects?

- Exploratory projects involve testing hypotheses and
finding patterns in data, while confirmatory projects
involve verifying existing hypotheses.
- Exploratory projects involve analyzing data that is
already structured, while confirmatory projects involve
analyzing unstructured data.

,- Exploratory projects involve analyzing large datasets,
while confirmatory projects involve analyzing smaller
datasets.
- Exploratory projects involve analyzing data from a
single source, while confirmatory projects involve
integrating data from multiple sources.
ANSWER-Exploratory projects involve testing
hypotheses and finding patterns in data, while
confirmatory projects involve verifying existing
hypotheses.
NOT CORRECT

Which project is considered a data analytics project?

- Developing a recommendation system to suggest new
products to customers based on their past purchases
- Creating a dashboard to visualize sales data and
monitor inventory levels for a grocery store chain
- Building a predictive model to forecast stock prices for
a financial services company
- Designing a database schema to store customer
information for a retail store
ANSWER-Creating a dashboard to visualize sales data
and monitor inventory levels for a grocery store chain

Why is quality control/assurance crucial for data
engineers in a data analytics project?

- It ensures that the data is analyzed in a timely manner.

,- It ensures that the data is stored in a secure location.
- It ensures that the data is accurate and reliable.
- It ensures that the data is accessible to all stakeholders.
ANSWER-It ensures that the data is accurate and
reliable.

What does a data analyst do in a data analytics project?

- Conducts exploratory data analysis to identify trends
and patterns
- Focuses on building machine learning models
- Oversees data governance and data quality assurance
- Designs and develops databases and data pipelines
ANSWER-Conducts exploratory data analysis to
identify trends and patterns

What is the function of a data scientist in an
organization?

- To design and maintain data visualizations and
dashboards
- To oversee data governance and compliance
- To work independently to analyze data and make
decisions based on their findings
- To conduct statistical analysis and machine learning
modeling
ANSWER-To conduct statistical analysis and machine
learning modeling

, What is the role of a business intelligence analyst?
- Overseeing data governance and compliance
- Developing and implementing data processing pipelines
- Designing and maintaining data visualizations and
dashboards
- Conducting statistical analysis and machine learning
modeling
ANSWER-Designing and maintaining data
visualizations and dashboards

What is a primary responsibility of a data engineer?
- Designing and implementing data storage solutions
- Designing and developing data visualizations for
stakeholders
- Analyzing and interpreting data to inform business
decisions
- Developing predictive models using machine learning
algorithms
ANSWER-Designing and implementing data storage
solutions

What is a primary responsibility of a machine learning
engineer?
- Developing predictive models using machine learning
algorithms
- Analyzing and interpreting data to inform business
decisions
- Designing and developing data visualizations for
stakeholders

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