WGU D491 Introduction to Analytics Actual Questions and Answers 100% Correct Already Graded A+
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WGU D491 Introduction to Analytics Actual Questio
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WGU D491 Introduction To Analytics Actual Questio
WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
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.
, WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
-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.)
, WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
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.
, WGU D491 Introduction to Analytics Actual
Questions and Answers 100% Correct Already
Graded A+
-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.
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