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Big Data in Engineering Applications (Hardcover, 1st ed. 2018): Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros... Big Data in Engineering Applications (Hardcover, 1st ed. 2018)
Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras
R5,240 Discovery Miles 52 400 Ships in 12 - 17 working days

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

Big Data in Engineering Applications (Paperback, Softcover reprint of the original 1st ed. 2018): Sanjiban Sekhar Roy, Pijush... Big Data in Engineering Applications (Paperback, Softcover reprint of the original 1st ed. 2018)
Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras
R5,456 Discovery Miles 54 560 Ships in 10 - 15 working days

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

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