D491 INTRODUCTION TO ANALYTICS EXAM WITH
CORRECT ACTUAL QUESTIONS AND CORRECTLY
WELL DEFINED ANSWERS
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Terms in this set (162)
What is Data analytics? The process of analyzing data to extract insights.
-The process of encrypting data to (Data analytics involves analyzing data to extract
keep it secure insights and inform decision-making. This includes
-The process of storing data in a using various techniques and tools to explore, clean,
secure location for future use transform, and model data and visualize and
-The process of analyzing data to communicate findings.)
extract insights
-The process of collecting data from
various sources
,What is data science? The practice of using statistical methods to extract
-A field that involves creating data insights from data. (Data science is a
visualizations to provide insights multidisciplinary field involving various statistical,
-The process of creating computer mathematical, and computational methods to
programs to automate tasks extract meaningful insights and knowledge from
-The study of how computers interact data.)
with human language
-The practice of using statistical
methods to extract insights from data
How is data science different from Data science focuses on developing new algorithms
data analytics? and models, while data analytics focuses on using
-Data science focuses more on data existing models to analyze data. (Data science is
visualization, while data analytics more research-based, while data analytics is more
focuses on data cleaning and focused on the practical applications of data
preprocessing. analytics.)
-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.
,Which comparison describes the Data analytics is the process of analyzing data to
difference between data analytics extract insights, while data science involves building
and data science? and testing models to make predictions. (Data
-Data analytics focuses on statistics, analytics involves using statistical and quantitative
and data science mainly focuses on methods to analyze data to extract insights and
qualitative reasoning. solve problems, while data science involves using
-Data science involves analyzing data machine learning and statistical models to build
from structured sources, while data predictive models and make decisions based on
analytics involves analyzing data from data.)
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.
Which type of data analytics project Descriptive (Descriptive analytics focuses on
aims to determine why something summarizing past events and understanding what
happened in the past? happened.)
-Prescriptive
-Descriptive
-Predictive
-Diagnostic
What are the different types of data Descriptive, diagnostic, predictive, and prescriptive
analytics projects? analytics
-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
, What is the difference between Exploratory projects involve testing hypotheses and
exploratory and confirmatory data finding patterns in data, while confirmatory projects
analytics projects? involve verifying existing hypotheses. (Exploratory
-Exploratory projects involve testing data analytics projects are typically used when little
hypotheses and finding patterns in is known about the data or when researchers look
data, while confirmatory projects for patterns or trends that may not have been
involve verifying existing hypotheses. previously identified.)
-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.
Which project is considered a data Creating a dashboard to visualize sales data and
analytics project? monitor inventory levels for a grocery store chain. (A
-Developing a recommendation data analytics project typically involves analyzing
system to suggest new products to data to identify trends and patterns and then using
customers based on their past this information to make data-driven decisions.)
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
CORRECT ACTUAL QUESTIONS AND CORRECTLY
WELL DEFINED ANSWERS
Play your way to mastery with fun games
Match Blocks Charms NEW
Terms in this set (162)
What is Data analytics? The process of analyzing data to extract insights.
-The process of encrypting data to (Data analytics involves analyzing data to extract
keep it secure insights and inform decision-making. This includes
-The process of storing data in a using various techniques and tools to explore, clean,
secure location for future use transform, and model data and visualize and
-The process of analyzing data to communicate findings.)
extract insights
-The process of collecting data from
various sources
,What is data science? The practice of using statistical methods to extract
-A field that involves creating data insights from data. (Data science is a
visualizations to provide insights multidisciplinary field involving various statistical,
-The process of creating computer mathematical, and computational methods to
programs to automate tasks extract meaningful insights and knowledge from
-The study of how computers interact data.)
with human language
-The practice of using statistical
methods to extract insights from data
How is data science different from Data science focuses on developing new algorithms
data analytics? and models, while data analytics focuses on using
-Data science focuses more on data existing models to analyze data. (Data science is
visualization, while data analytics more research-based, while data analytics is more
focuses on data cleaning and focused on the practical applications of data
preprocessing. analytics.)
-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.
,Which comparison describes the Data analytics is the process of analyzing data to
difference between data analytics extract insights, while data science involves building
and data science? and testing models to make predictions. (Data
-Data analytics focuses on statistics, analytics involves using statistical and quantitative
and data science mainly focuses on methods to analyze data to extract insights and
qualitative reasoning. solve problems, while data science involves using
-Data science involves analyzing data machine learning and statistical models to build
from structured sources, while data predictive models and make decisions based on
analytics involves analyzing data from data.)
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.
Which type of data analytics project Descriptive (Descriptive analytics focuses on
aims to determine why something summarizing past events and understanding what
happened in the past? happened.)
-Prescriptive
-Descriptive
-Predictive
-Diagnostic
What are the different types of data Descriptive, diagnostic, predictive, and prescriptive
analytics projects? analytics
-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
, What is the difference between Exploratory projects involve testing hypotheses and
exploratory and confirmatory data finding patterns in data, while confirmatory projects
analytics projects? involve verifying existing hypotheses. (Exploratory
-Exploratory projects involve testing data analytics projects are typically used when little
hypotheses and finding patterns in is known about the data or when researchers look
data, while confirmatory projects for patterns or trends that may not have been
involve verifying existing hypotheses. previously identified.)
-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.
Which project is considered a data Creating a dashboard to visualize sales data and
analytics project? monitor inventory levels for a grocery store chain. (A
-Developing a recommendation data analytics project typically involves analyzing
system to suggest new products to data to identify trends and patterns and then using
customers based on their past this information to make data-driven decisions.)
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
