Mastering Big Data Analytics with Hadoop: From Basics to Advanced Techniques

“Mastering Big Data Analytics with Hadoop” offers a comprehensive theoretical exploration of big data and its analytics through the lens of the Hadoop ecosystem. This book begins by defining big data, examining its characteristics, and discussing the challenges it poses across various sectors.
Readers will gain a deep understanding of Hadoop’s architecture, including the roles of HDFS (Hadoop Distributed File System) and MapReduce in managing and processing extensive datasets. The text delves into essential concepts of data processing, contrasting batch processing with stream processing while emphasizing the importance of data ingestion, cleaning, and transformation.
Furthermore, the book explores various analytical frameworks and tools that enhance Hadoop’s capabilities, such as Hive, Pig, and Spark, detailing their theoretical foundations and applications. It also addresses statistical methods and algorithms commonly employed in big data analytics, including regression, clustering, and classification.
In addition to technical aspects, the book discusses data governance, privacy, and ethical considerations, underscoring their significance in the realm of big data analytics. This resource is ideal for anyone seeking a solid theoretical foundation in big data and Hadoop, paving the way for practical application and advanced study.