Titre : |
Big Data and business analytics |
Type de document : |
texte imprimé |
Auteurs : |
Jay Liebowitz ; Jay Liebowitz, Éditeur scientifique ; Joe LaCugna, |
Editeur : |
Boca Raton, FL : Auerbach Publications |
Année de publication : |
2013 |
Importance : |
XXI-282 p. |
Présentation : |
fig., tabl. |
Format : |
25 cm |
ISBN/ISSN/EAN : |
978-1-4665-6578-4 |
Note générale : |
Index |
Langues : |
Anglais (eng) |
Descripteurs : |
Données massives , Entrepôt de données , Fouille de données
|
Index. décimale : |
239 Fouille de données - Data mining |
Résumé : |
This book offers useful case studies, technical roadmaps, lessons learned, and a few prescriptions to "do this, avoid that". It's helpful for quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive. It assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation. It's useful to understand the trends, potential, and challenges associated with big data and business analytics, to get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues. Big data problems are complex, so this book shows how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage. It also contains case studies from big data domains such as cybersecurity, finance, emergency management, marketing, healthcare, and international development; it gives overviews of machine learning and advanced statistical techniques to help readers solve big data issues; it allows CEOs and senior managers to quickly grasp key factors and trends to make their organizations more competitive and explains how business analytics can guide executive decision making. [D'après le résumé de l'éditeur] |
Note de contenu : |
Paperback (2016) = ISBN-13: 978-1498774796 |
En ligne : |
http://www.crcpress.com/product/isbn/9781466565784 |
Permalink : |
https://genes.bibli.fr/index.php?lvl=notice_display&id=107970 |
Big Data and business analytics [texte imprimé] / Jay Liebowitz ; Jay Liebowitz, Éditeur scientifique ; Joe LaCugna, . - Boca Raton, FL : Auerbach Publications, 2013 . - XXI-282 p. : fig., tabl. ; 25 cm. ISBN : 978-1-4665-6578-4 Index Langues : Anglais ( eng)
Descripteurs : |
Données massives , Entrepôt de données , Fouille de données
|
Index. décimale : |
239 Fouille de données - Data mining |
Résumé : |
This book offers useful case studies, technical roadmaps, lessons learned, and a few prescriptions to "do this, avoid that". It's helpful for quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive. It assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation. It's useful to understand the trends, potential, and challenges associated with big data and business analytics, to get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues. Big data problems are complex, so this book shows how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage. It also contains case studies from big data domains such as cybersecurity, finance, emergency management, marketing, healthcare, and international development; it gives overviews of machine learning and advanced statistical techniques to help readers solve big data issues; it allows CEOs and senior managers to quickly grasp key factors and trends to make their organizations more competitive and explains how business analytics can guide executive decision making. [D'après le résumé de l'éditeur] |
Note de contenu : |
Paperback (2016) = ISBN-13: 978-1498774796 |
En ligne : |
http://www.crcpress.com/product/isbn/9781466565784 |
Permalink : |
https://genes.bibli.fr/index.php?lvl=notice_display&id=107970 |
| |