Handbook of big data research methods:
This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of...
Gespeichert in:
Weitere Verfasser: | , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cheltenham, UK ; Northampton, Massachusetts, USA
Edward Elgar Publishing
[2023]
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Schriftenreihe: | Research handbooks in information systems
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Schlagworte: | |
Online-Zugang: | DE-634 DE-188 DE-863 DE-862 DE-91 DE-355 DE-945 DE-29 Volltext |
Zusammenfassung: | This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics. With contributions from leading academics and practitioners, the Handbook analyses how big data analytics can be used in different sectors, including detecting credit fraud in the financial sector, identifying potential diseases in health care, and increasing customer loyalty in the telecommunication sector. Chapters explore the use of artificial intelligence in accounting, the construction of successful data science ecosystems using the public cloud, and transformational models of personal data protection in the digital era. The Handbook also discusses the difficulties of adopting a data science platform and how the public cloud can aid companies in overcoming these challenges. Exploring how industries rely on predictive analytics to improve their decision-making, this Handbook will be essential reading for students and scholars in business analytics, economics, information systems, innovation and technology, and research methods. It will also benefit data analysts, economists, human resource managers, marketers, neuroscientists, and social science researchers. |
Beschreibung: | Titel und Verantwortlichkeitsangabe der Landingpage (Elgaronline) entnommen, da kein Titelblatt vorhanden |
Beschreibung: | 1 Online-Ressource (xi, 322 Seiten) Illustrationen, Diagramme, Karten |
ISBN: | 9781800888555 |
DOI: | 10.4337/9781800888555 |
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Datensatz im Suchindex
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spellingShingle | Handbook of big data research methods Künstliche Intelligenz (DE-588)4033447-8 gnd Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
subject_GND | (DE-588)4033447-8 (DE-588)4802620-7 (DE-588)4123037-1 (DE-588)4428654-5 (DE-588)4143413-4 |
title | Handbook of big data research methods |
title_auth | Handbook of big data research methods |
title_exact_search | Handbook of big data research methods |
title_exact_search_txtP | Handbook of big data research methods |
title_full | Handbook of big data research methods edited by Shahriar Akter and Samuel Fosso Wamba |
title_fullStr | Handbook of big data research methods edited by Shahriar Akter and Samuel Fosso Wamba |
title_full_unstemmed | Handbook of big data research methods edited by Shahriar Akter and Samuel Fosso Wamba |
title_short | Handbook of big data research methods |
title_sort | handbook of big data research methods |
topic | Künstliche Intelligenz (DE-588)4033447-8 gnd Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
topic_facet | Künstliche Intelligenz Big Data Datenanalyse Data Mining Aufsatzsammlung |
url | https://doi.org/10.4337/9781800888555 |
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