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Enjeux & Défis du Big Data: Défis Épistémologiques des Mégadonnées

Enjeux & Défis du Big Data: Défis Épistémologiques des Mégadonnées

          
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About the Book

Les enjeux et défis du Big Data, appelé aussi données massives, ne sont pas seulement économiques, politiques ou éthiques mais aussi épistémologiques inédits et inévitables pour pouvoir bien valoriser ces données prometteuses. La contribution de ces données massives ou mégadonnées représente 5% à 6% de la productivité enregistrée pour les entreprises qui adoptent une prise de décision basée sur les mégadonnées, d'après le rapport de 2014 par le Massachusetts Institute of Technology (MIT). Le rapport de 2011 par McKinsey Global Institute (MGI) prévoit des améliorations encore plus substantielles et plus importantes à venir dans le futur proche. En termes d'éthique, en Europe un règlement général sur la protection des données (RGPD) a été déjà élaboré et il est appliqué dans l'Union Européenne à partir du 25 mai 2018. Le RGPD s'applique à toute organisation qui traite des données personnelles des citoyens, aussi bien que des résidents partout en Europe. Il permet aux citoyens et résidents un contrôle sur leurs données à caractère personnel et en même temps aux entreprises de bénéficier de conditions de concurrence équitables. Cependant, à mesure que ces mégadonnées augmentent massivement et rapidement elles créent également des enjeux et des défis épistémologiques avec de nouvelles controverses telles que la question de savoir si ces mégadonnées peuvent rendre la science obsolète? Ce livre se consacre aux enjeux et défis épistémologiques des mégadonnées, depuis leur acquisition jusqu'à leur analyse et prise de décisions. Il se réfère au travail épistémologique de Gaston Bachelard pour aider dans les processus d'acquisition et d'analyse de ces données massives. Gaston Bachelard nous rappelle la vigilance pour bien valoriser les données et générer des connaissances pour appuyer des applications pratiques, y inclus les solutions d'Intelligence Artificielle et les solutions durables.On trouve aussi dans le livre plusieurs cas pratiques du Big Data en relation avec l'Intelligence Artificielle et les solutions durables. Je cite, comme cas pratique que je conduisais avec les collègues, l'exemple qui évoque l'approche de Gaston Bachelard et de Pierre-Simon de Laplace pour identifier des gènes. Le livre souligne également l'importance de faire face à la pénurie des talents sans précédent, perturbant le marché du travail presque dans tous les pays.


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Product Details
  • ISBN-13: 9781983383052
  • Publisher: Amazon Digital Services LLC - KDP Print US
  • Publisher Imprint: Independently Published
  • Height: 229 mm
  • No of Pages: 204
  • Spine Width: 12 mm
  • Weight: 304 gr
  • ISBN-10: 1983383058
  • Publisher Date: 07 Jul 2018
  • Binding: Paperback
  • Language: French
  • Returnable: N
  • Sub Title: Défis Épistémologiques des Mégadonnées
  • Width: 152 mm


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