Question
Explain the scope and objectives of Data Science. Discuss the importance of data collection and sampling techniques in data-driven decision making. Illustrate your answer with suitable examples.
Answer :
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Data Science is an interdisciplinary field that combines statistics, mathematics, computer science, machine learning, artificial intelligence, and domain knowledge to extract meaningful insights from structured and unstructured data. It enables organizations to analyze large volumes of data, identify patterns, predict future trends, and support evidence-based decision making. With the rapid growth of digital technologies, cloud computing, Internet of Things (IoT), and social media platforms, Data Science has become a fundamental component of modern businesses, governments, healthcare systems, scientific research, and education. The scope of Data Science is extensive and continuously expanding. It includes data collection, data storage, data cleaning, data integration, exploratory data analysis, statistical modeling, machine learning, data visualization, and deployment of predictive models. Data Science also involves handling big data using technologies such as Hadoop and Spark, processing real-time ________ _________ _________ ___ _________ __________ _________ ____ ________.
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Data Science is an interdisciplinary field that combines statistics, mathematics, computer science, machine learning, artificial intelligence, and domain knowledge to extract meaningful insights from structured and unstructured data. It enables organizations to analyze large volumes of data, identify patterns, predict future trends, and support evidence-based decision making. With the rapid growth of digital technologies, cloud computing, Internet of Things (IoT), and social media platforms, Data Science has become a fundamental component of modern businesses, governments, healthcare systems, scientific research, and education. The scope of Data Science is extensive and continuously expanding. It includes data collection, data storage, data cleaning, data integration, exploratory data analysis, statistical modeling, machine learning, data visualization, and deployment of predictive models. Data Science also involves handling big data using technologies such as Hadoop and Spark, processing real-time ________ _________ _________ ___ _________ __________ _________ ____ ________.
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