This book is intended to serve as a useful academic and technical resource for undergraduate students, postgraduate students, research scholars, faculty members, and professionals who wish to understand the foundations of modern data-intensive computing. The chapters are organized in a simple and systematic manner so that learners can gradually move from basic concepts to practical frameworks and real-world applications. The book begins with the fundamentals and applications of Big Data technologies, explaining the characteristics, sources, importance, and emerging trends of Big Data. It then discusses Hadoop, MapReduce, and HDFS architecture, which form the backbone of distributed storage and processing in large-scale data environments.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. This book is intended to serve as a useful academic and technical resource for undergraduate students, postgraduate students, research scholars, faculty members, and professionals who wish to understand the foundations of modern data-intensive computing. The chapters are organized in a simple and systematic manner so that learners can gradually move from basic concepts to practical frameworks and real-world applications. The book begins with the fundamentals and applications of Big Data technologies, explaining the characteristics, sources, importance, and emerging trends of Big Data. It then discusses Hadoop, MapReduce, and HDFS architecture, which form the backbone of distributed storage and processing in large-scale data environments. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798905604386
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Hardcover. Etat : new. Hardcover. This book is intended to serve as a useful academic and technical resource for undergraduate students, postgraduate students, research scholars, faculty members, and professionals who wish to understand the foundations of modern data-intensive computing. The chapters are organized in a simple and systematic manner so that learners can gradually move from basic concepts to practical frameworks and real-world applications. The book begins with the fundamentals and applications of Big Data technologies, explaining the characteristics, sources, importance, and emerging trends of Big Data. It then discusses Hadoop, MapReduce, and HDFS architecture, which form the backbone of distributed storage and processing in large-scale data environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798905604386
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Hardcover. Etat : new. Hardcover. This book is intended to serve as a useful academic and technical resource for undergraduate students, postgraduate students, research scholars, faculty members, and professionals who wish to understand the foundations of modern data-intensive computing. The chapters are organized in a simple and systematic manner so that learners can gradually move from basic concepts to practical frameworks and real-world applications. The book begins with the fundamentals and applications of Big Data technologies, explaining the characteristics, sources, importance, and emerging trends of Big Data. It then discusses Hadoop, MapReduce, and HDFS architecture, which form the backbone of distributed storage and processing in large-scale data environments. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9798905604386
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Buch. Etat : Neu. Big Data Technologies and NoSQL Databases | Fundamentals, Architecture, and Applications | Jenifer Mahilraj (u. a.) | Buch | Englisch | 2026 | Notion Press | EAN 9798905604386 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 136342368
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