Big Data Analytics: A Management Perspective

Big Data Analytics: A Management Perspective

AngličtinaPevná vazbaTisk na objednávku
Corea Francesco
Springer, Berlin
EAN: 9783319389912
Tisk na objednávku
Předpokládané dodání v pondělí, 10. února 2025
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Podrobné informace

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.
EAN 9783319389912
ISBN 3319389912
Typ produktu Pevná vazba
Vydavatel Springer, Berlin
Datum vydání 29. září 2016
Stránky 48
Jazyk English
Rozměry 235 x 155
Země Switzerland
Sekce General
Autoři Corea Francesco
Ilustrace XIII, 48 p. 7 illus. in color.
Edice 1st ed. 2016
Série Studies in Big Data