Introduction to Analytics - D491 Questions and
Verified 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.)
What is the function of a data scientist in an organization?
-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
-To design and maintain data visualizations and dashboards - ANSWER To conduct
statistical analysis and machine learning modeling. (Data scientists analyze complex datasets
using statistical analysis and machine learning techniques. This typically involves cleaning
and preprocessing data, conducting exploratory data analysis, building and testing models,
and communicating insights to business stakeholders.)
What is the role of a business intelligence analyst?
-Designing and maintaining data visualizations and dashboards
-Conducting statistical analysis and machine learning modeling
-Developing and implementing data processing pipelines
-Overseeing data governance and compliance - ANSWER Designing and maintaining data
visualizations and dashboards. (Business intelligence analysts are responsible for designing
and maintaining data visualizations and dashboards to communicate business insights to
stakeholders.)
What is a primary responsibility of a data engineer?
-Designing and developing data visualizations for stakeholders
-Designing and implementing data storage solutions
-Analyzing and interpreting data to inform business decisions
-Developing predictive models using machine learning algorithms - ANSWER Designing and
implementing data storage solutions. (Data engineers are responsible for designing and
Verified 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.)
What is the function of a data scientist in an organization?
-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
-To design and maintain data visualizations and dashboards - ANSWER To conduct
statistical analysis and machine learning modeling. (Data scientists analyze complex datasets
using statistical analysis and machine learning techniques. This typically involves cleaning
and preprocessing data, conducting exploratory data analysis, building and testing models,
and communicating insights to business stakeholders.)
What is the role of a business intelligence analyst?
-Designing and maintaining data visualizations and dashboards
-Conducting statistical analysis and machine learning modeling
-Developing and implementing data processing pipelines
-Overseeing data governance and compliance - ANSWER Designing and maintaining data
visualizations and dashboards. (Business intelligence analysts are responsible for designing
and maintaining data visualizations and dashboards to communicate business insights to
stakeholders.)
What is a primary responsibility of a data engineer?
-Designing and developing data visualizations for stakeholders
-Designing and implementing data storage solutions
-Analyzing and interpreting data to inform business decisions
-Developing predictive models using machine learning algorithms - ANSWER Designing and
implementing data storage solutions. (Data engineers are responsible for designing and
