Big Data in Finance: Transforming the Financial Landscape - Volume 1

This book offers a comprehensive exploration of how Big Data analytics is reshaping the financial world, providing crucial insights for industry professionals, scholars, and enthusiasts alike. This book delves into the expansive potential of Big Data in revolutionizing financial decision-making, risk management, and operational efficiency. It explores how advanced analytics, machine learning, and artificial intelligence are disrupting traditional financial models, empowering institutions with unparalleled insights and a competitive edge. While highlighting technological advancements, the book also addresses the challenges and ethical considerations inherent in data-driven finance. With contributions from leading experts and thought leaders, this book serves as an indispensable resource for anyone eager to understand and harness the transformative power of Big Data in finance. Embark on a journey through the dynamic convergence of finance and technology, and discover how Big Data is shaping the future of the financial landscape, one data point at a time.

Inhaltsverzeichnis

Impact of employee engagement on job performance of IT employees.- Investigating Value Added Tax and customs duties on Retail Supply Chains in Clothing Industry.- Impact of Life Cycle Cost of Airfield Pavement on Airport Operations.- The Impact of Internal Marketing on Organizational Performance in UAE Healthcare Settings.

Produktdetails

• Mitarbeit: Bahaaeddin Alareeni (Herausgeber)
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Fester Einband
• Erschienen: 23.12.2024
• EAN: 9783031750946
• ISBN: 978-3-0-3175094-6
• Seiten: 756
• Abmessung: 155 mm x 45 mm x 235 mm
• Gewicht: 1252 g
• Illustration: XIII, 756 p. 131 illus., 105 illus. in color.
• Serie: Studies in Big Data
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Technik > Allgemeines, Lexika; Case Studies, Big Data, machine learning, Digital Transformation, Artificial Intelligence, Finance, personalization, Angewandte Mathematik, Data Privacy, Predictive Analytics, Data Analytics, risk management, financial markets, Data Engineering, Mathematics in Business, Economics and Finance, Customer Insights, Regulatory compliance, Real-World Applications, Operational efficiency, Financial Decision-Making, Market Trends, Fraud Detection, Technological Advancements