100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Previously searched by you
Previously searched by you
logo
Introduction to Analytics - D491 questions and answers latest top score. $11.99
Add to cart
Quickly navigate to
Preview
  2.  
  3. Introduction To Analytics - D491
  4.  
  5. Introduction to Analytics - D491

Exam (elaborations)

Introduction to Analytics - D491 questions and answers latest top score.
 0 purchase
  • Course
  • Introduction to Analytics - D491
  • Institution
  • Introduction To Analytics - D491

Introduction to Analytics - D491 questions and answers latest top score. 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 proces...

[Show more]

Preview 3 out of 30  pages

Document information

  • January 5, 2024
  • 30
  • 2023/2024
  • Exam (elaborations)
  • Questions & answers

Subjects

  • introduction to analytics d491 questions

Written for

  • Introduction to Analytics - D491
  • Introduction to Analytics - D491

Seller

avatar-seller
techgrades

Reviews received

Content preview

Introduction to Analytics - D491 questions and answers latest top score. 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 da ta from various sources - correct answers.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, transfo rm, 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 wit h human language -The practice of using statistical methods to extract insights from data - correct answers.The practice of using statistical methods to extract insights from data. (Data science is a multidisciplinary field involving various statistical, m athematical, 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 in volves 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. - correct answers.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 compari son 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 sci ence focuses on prescriptive analysis. - correct answers.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 quanti tative 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 det ermine why something happened in the past? -Prescriptive -Descriptive -Predictive -Diagnostic - correct answers.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 colle ction, data cleaning, data transformation, and data visualization - correct answers.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 multipl e 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 small er datasets. - correct answers.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 abo ut 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 price s for a financial services company -Designing a database schema to store customer information for a retail store - correct answers.Creating a dashboard to visualize sales data and monitor inventory levels for a grocery store chain. (A data analytics projec t 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 accur ate 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. - correct answers.It ensures that the data is accurate and re liable. (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 - correct answers.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 ma chine learning modeling -To design and maintain data visualizations and dashboards - correct answers.To conduct statistical analysis and machine learning modeling. (Data scientists analyze complex datasets using statistical analysis and machine learning te chniques. This typically involves cleaning and preprocessing data, conducting exploratory data

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller techgrades. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $11.99. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

69252 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 15 years now

Start selling
$11.99
  • (0)
Add to cart
Added