INTRODUCTION TO ANALYTICS - D491 WGU | 162
QUESTIONS | WITH ALL PASSED SOLUTIONS!!
What is Data analytics?
-The process of encrypting data to keep it secure
-The process of storing data in a secure location for future use
-The process of analyzing data to extract insights
-The process of collecting data from various sources Answer - The process of
analyzing data to extract insights. (Data analytics involves analyzing data to
extract insights and inform decision-making. This includes using various
techniques and tools to explore, clean, transform, and model data and visualize
and communicate findings.)
What is data science?
-A field that involves creating data visualizations to provide insights
-The process of creating computer programs to automate tasks
-The study of how computers interact with human language
-The practice of using statistical methods to extract insights from data Answer -
The practice of using statistical methods to extract insights from data. (Data
science is a multidisciplinary field involving various statistical, mathematical,
and computational methods to extract meaningful insights and knowledge
from data.)
How is data science different from data analytics?
-Data science focuses more on data visualization, while data analytics focuses
on data cleaning and preprocessing.
,-Data science focuses more on tracking experimental data, and data analytics is
based on statistical methods and hypotheses.
-Data science involves creating new algorithms, while data analytics uses
existing statistical methods.
-Data science focuses on developing new algorithms and models, while data
analytics focuses on using existing models to analyze data. Answer - Data
science focuses on developing new algorithms and models, while data analytics
focuses on using existing models to analyze data. (Data science is more
research-based, while data analytics is more focused on the practical
applications of data analytics.)
Which comparison describes the difference between data analytics and data
science?
-Data analytics focuses on statistics, and data science mainly focuses on
qualitative reasoning.
-Data science involves analyzing data from structured sources, while data
analytics involves analyzing data from unstructured sources.
-Data analytics is the process of analyzing data to extract insights, while data
science involves building and testing models to make predictions.
-Data analytics focuses on descriptive analysis, while data science focuses on
prescriptive analysis. Answer - Data analytics is the process of analyzing data
to extract insights, while data science involves building and testing models to
make predictions. (Data analytics involves using statistical and quantitative
methods to analyze data to extract insights and solve problems, while data
science involves using machine learning and statistical models to build
predictive models and make decisions based on data.)
Which type of data analytics project aims to determine why something
happened in the past?
-Prescriptive
-Descriptive
-Predictive
, -Diagnostic Answer - Descriptive (Descriptive analytics focuses on
summarizing past events and understanding what happened.)
What are the different types of data analytics projects?
-Regression analysis, time series analysis, text analytics, and network analysis
-Data warehousing, data mining, data visualization, and business intelligence
-Descriptive, diagnostic, predictive, and prescriptive analytics
-Data collection, data cleaning, data transformation, and data visualization
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 from a single source, while
confirmatory projects involve integrating data from multiple sources.
-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. Answer - Exploratory projects
involve testing hypotheses and finding patterns in data, while confirmatory
projects involve verifying existing hypotheses. (Exploratory data analytics
projects are typically used when little is known about the data or when
researchers look for patterns or trends that may not have been previously
identified.)
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. (A data analytics project typically involves
analyzing data to identify trends and patterns and then using this information
to make data-driven decisions.)
Why is quality control/assurance crucial for data engineers in a data analytics
project?
-It ensures that the data is accurate and reliable.
-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 accessible to all stakeholders. Answer - It ensures
that the data is accurate and reliable. (Quality control is crucial for data
engineers in a data analytics project because it ensures that the data used for
analysis is accurate and reliable.)
What does a data analyst do in a data analytics project?
-Focuses on building machine learning models
-Conducts exploratory data analysis to identify trends and patterns
-Designs and develops databases and data pipelines
-Oversees data governance and data quality assurance Answer - Conducts
exploratory data analysis to identify trends and patterns. (Data analysts are
responsible for analyzing data to identify trends and patterns that can inform
business decisions. This typically involves conducting exploratory data analysis,
which involves visually exploring and summarizing data to identify patterns and
relationships.)
QUESTIONS | WITH ALL PASSED SOLUTIONS!!
What is Data analytics?
-The process of encrypting data to keep it secure
-The process of storing data in a secure location for future use
-The process of analyzing data to extract insights
-The process of collecting data from various sources Answer - The process of
analyzing data to extract insights. (Data analytics involves analyzing data to
extract insights and inform decision-making. This includes using various
techniques and tools to explore, clean, transform, and model data and visualize
and communicate findings.)
What is data science?
-A field that involves creating data visualizations to provide insights
-The process of creating computer programs to automate tasks
-The study of how computers interact with human language
-The practice of using statistical methods to extract insights from data Answer -
The practice of using statistical methods to extract insights from data. (Data
science is a multidisciplinary field involving various statistical, mathematical,
and computational methods to extract meaningful insights and knowledge
from data.)
How is data science different from data analytics?
-Data science focuses more on data visualization, while data analytics focuses
on data cleaning and preprocessing.
,-Data science focuses more on tracking experimental data, and data analytics is
based on statistical methods and hypotheses.
-Data science involves creating new algorithms, while data analytics uses
existing statistical methods.
-Data science focuses on developing new algorithms and models, while data
analytics focuses on using existing models to analyze data. Answer - Data
science focuses on developing new algorithms and models, while data analytics
focuses on using existing models to analyze data. (Data science is more
research-based, while data analytics is more focused on the practical
applications of data analytics.)
Which comparison describes the difference between data analytics and data
science?
-Data analytics focuses on statistics, and data science mainly focuses on
qualitative reasoning.
-Data science involves analyzing data from structured sources, while data
analytics involves analyzing data from unstructured sources.
-Data analytics is the process of analyzing data to extract insights, while data
science involves building and testing models to make predictions.
-Data analytics focuses on descriptive analysis, while data science focuses on
prescriptive analysis. Answer - Data analytics is the process of analyzing data
to extract insights, while data science involves building and testing models to
make predictions. (Data analytics involves using statistical and quantitative
methods to analyze data to extract insights and solve problems, while data
science involves using machine learning and statistical models to build
predictive models and make decisions based on data.)
Which type of data analytics project aims to determine why something
happened in the past?
-Prescriptive
-Descriptive
-Predictive
, -Diagnostic Answer - Descriptive (Descriptive analytics focuses on
summarizing past events and understanding what happened.)
What are the different types of data analytics projects?
-Regression analysis, time series analysis, text analytics, and network analysis
-Data warehousing, data mining, data visualization, and business intelligence
-Descriptive, diagnostic, predictive, and prescriptive analytics
-Data collection, data cleaning, data transformation, and data visualization
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 from a single source, while
confirmatory projects involve integrating data from multiple sources.
-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. Answer - Exploratory projects
involve testing hypotheses and finding patterns in data, while confirmatory
projects involve verifying existing hypotheses. (Exploratory data analytics
projects are typically used when little is known about the data or when
researchers look for patterns or trends that may not have been previously
identified.)
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. (A data analytics project typically involves
analyzing data to identify trends and patterns and then using this information
to make data-driven decisions.)
Why is quality control/assurance crucial for data engineers in a data analytics
project?
-It ensures that the data is accurate and reliable.
-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 accessible to all stakeholders. Answer - It ensures
that the data is accurate and reliable. (Quality control is crucial for data
engineers in a data analytics project because it ensures that the data used for
analysis is accurate and reliable.)
What does a data analyst do in a data analytics project?
-Focuses on building machine learning models
-Conducts exploratory data analysis to identify trends and patterns
-Designs and develops databases and data pipelines
-Oversees data governance and data quality assurance Answer - Conducts
exploratory data analysis to identify trends and patterns. (Data analysts are
responsible for analyzing data to identify trends and patterns that can inform
business decisions. This typically involves conducting exploratory data analysis,
which involves visually exploring and summarizing data to identify patterns and
relationships.)
