Guide to Big Data Applications / edited by S. Srinivasan.
Contributor(s): Srinivasan, S, editor literario
Material type:
E-bookSeries: (Studies in Big Data, 2197-6503; 26); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing, 2018Description: 1 recurso en línea (XVII, 565 páginas 205 ilustraciones, 155 ilustraciones a color).ISBN: 9783319538174.Subject: Datos masivos
| Arquitectura de redes informáticasOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.B45 G853 2018 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.15112850 |
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| QA76.9.B45 E447 2017 EB Emerging technology and architecture for big-data analytics | QA76.9.B45 E845 2016 EB Ethical Reasoning in Big Data : An Exploratory Analysis | QA76.9.B45 .F87 2016 EB Big Data Technologies and Applications | QA76.9.B45 G853 2018 EB Guide to Big Data Applications | QA76.9.B45 H544 2018 EB Highlighting the Importance of Big Data Management and Analysis for Various Applications | QA76.9 .B45 N494 2016 EB New Horizons for a Data-Driven Economy : A Roadmap for Usage and Exploitation of Big Data in Europe | QA76.9 .B45 O64 2016 EB Weapons of math destruction : how big data increases inequality and threatens democracy |
Introduction -- Big Data Analytics -- Big Data and Social Media -- Use of Cloud Computing for Big Data in Business -- Economic Data Analysis Related to Developing Countries -- High Performance Computing and Big Data -- Big Data Applications in Physics -- Big Data Applications in Chemistry -- Big Data Applications in Mathematics -- Big Data Applications in Biology -- Big Data Applications in Engineering -- Big Data Applications in Meteorology -- Big Data Applications in Environmental Science -- Big Data Applications in Energy -- Security Applications for Big Data -- Big Data Applications in Network Traffic Analysis -- Big Data Applications in Supply Chain Logistics -- Big Data Applications in Healthcare -- Big Data Applications in Cancer Research -- Impact of Big Data in Marketing -- Use of Big Data in Banking -- Using Big Data for Fraud Detection in Accounting -- Using Big Data for Supply Chain Management -- Privacy Implications of Big Data -- Legal Perspectives of Big Data -- Ethical Handling of Big Data in Practical Uses -- Conclusion.
This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.
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