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