Big Data: Concepts, Technologies, and Applications offers a comprehensive and practical introduction to the principles and practices of Big Data analytics. Designed for students, researchers, and industry professionals, this book bridges the gap between theoretical foundations and real-world implementation.
The book begins with an overview of Big Data characteristics, challenges, and architectures, followed by detailed explanations of data storage, processing frameworks, and analytics models. Core technologies such as Hadoop, HDFS, MapReduce, Spark, NoSQL databases, and data streaming platforms are explained with clear examples and use-case-driven discussions. Emphasis is placed on scalable data processing, performance optimization, and fault tolerance in distributed environments.
In addition, the book explores data analytics techniques, machine learning integration, and Big Data applications across domains such as education, healthcare, business intelligence, and social media analytics. Special focus is given to student performance prediction and data-driven decision making, making this book highly relevant for academic research and real-world problem solving.
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