000			03363nam a22003495i 4500
001			102878
003			DE-He213
005			20230102113104.0
007			cr nn 008mamaa
008			170526s2018 gw | s |||| 0|eng d
020			_a9783319538174
024	7		_a10.1007/978-3-319-53817-4 _2doi
040			_aES-MaUEC _bspa
050		4	_aQA76.9.B45 _bG853 2018 EB
245	1	0	_aGuide to Big Data Applications _cedited by S. Srinivasan.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XVII, 565 páginas 205 ilustraciones, 155 ilustraciones a color)
347			_atext file _bPDF
490	0		_aStudies in Big Data _x2197-6503 _v26
505	0		_aIntroduction -- 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.
520	3		_aThis 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.
650		7	_aDatos masivos _9495511 _2embne
650		7	_aArquitectura de redes informáticas _9144553 _2embne
700	1		_aSrinivasan, S _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n2009074158 _1http://viaf.org/viaf/17284152/
776	0	8	_iEdición impresa: _z9783319538167
776	0	8	_iEdición impresa: _z9783319538181
776	0	8	_iEdición impresa: _z9783319852492
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-53817-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b02/2019 _dz _ek _feng _ggw _h0
999			_c102878 _d102878 _x1