Big Data in engineering applications Book / edited by Sanjiban Sekhar Roy, Pijush Samui, Ravinesh Deo, Stavros Ntalampiras.

Contributor(s):

Material type: Text

TextSeries: Studies in Big Data ; 44Description: 384 pages : 24 cmISBN:

9789811084751 (hardback)

Subject(s):

DDC classification:

006.3 23

Other classification:

006.3

Summary: 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 gingering 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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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Books	Junaid Zaidi Library, COMSATS University Islamabad Ground Floor	006.3 BIG 62035 (Browse shelf(Opens below))	Available		10001000062035

Total holds: 0

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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 gingering 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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