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WGU D491 INTRODUCTION TO ANALYTICS OBJECTIVE ASSESMENT EXAM ACTUAL EXAM AND STUDY GUIDE COMPLETE 450 QUESTIONS AND CORRECT VERIFIED SOLUTIONS LATEST $24.99
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WGU D491 INTRODUCTION TO ANALYTICS OBJECTIVE
ASSESMENT EXAM ACTUAL EXAM AND STUDY GUIDE
COMPLETE 450 QUESTIONS AND CORRECT VERIFIED
SOLUTIONS LATEST 2024-2025
WGU D491 INTRODUCTION TO ANALYTICS OA actual exam
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.)
QUESTION: 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
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field involving various statistical, mathematical, and computational methods to extract
meaningful insights and knowledge from data.)
QUESTION: 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.)
QUESTION: 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.
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-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.)
QUESTION: 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.)
QUESTION: 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
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QUESTION: 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.)
QUESTION: 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.)
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