Introduction to Analytics - D491 Exam (ACTUAL 2025/2026) Questions with Correct Answers| Latest Update 100% Solved | GRADED A+

Introduction to Analytics - D491 Exam (ACTUAL 2025/2026) Questions with Correct Answers| Latest Update 100% Solved | 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 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 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. -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. 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.)